- name
- create-agent-adapter
- description
- Create or modify Paperclip agent adapters across server, UI, and CLI surfaces. Use when adding support for a new CLI agent, API agent, custom process, or adapter package.
Creating a Paperclip Agent Adapter
An adapter bridges Paperclip's orchestration layer to a specific AI agent runtime (Claude Code, Codex CLI, a custom process, an HTTP endpoint, etc.). Each adapter is a self-contained package that provides implementations for three consumers: the server, the UI, and the CLI.
1. Architecture Overview
packages/adapters/<name>/
src/
index.ts # Shared metadata (type, label, models, agentConfigurationDoc)
server/
index.ts # Server exports: execute, sessionCodec, parse helpers
execute.ts # Core execution logic (AdapterExecutionContext -> AdapterExecutionResult)
parse.ts # Stdout/result parsing for the agent's output format
ui/
index.ts # UI exports: parseStdoutLine, buildConfig
parse-stdout.ts # Line-by-line stdout -> TranscriptEntry[] for the run viewer
build-config.ts # CreateConfigValues -> adapterConfig JSON for agent creation form
cli/
index.ts # CLI exports: formatStdoutEvent
format-event.ts # Colored terminal output for `paperclipai run --watch`
package.json
tsconfig.json
Three separate registries consume adapter modules:
2. Shared Types (@paperclipai/adapter-utils)
All adapter interfaces live in packages/adapter-utils/src/types.ts. Import from @paperclipai/adapter-utils (types) or @paperclipai/adapter-utils/server-utils (runtime helpers).
Core Interfaces
// The execute function signature — every adapter must implement this
interface AdapterExecutionContext {
runId: string;
agent: AdapterAgent; // { id, companyId, name, adapterType, adapterConfig }
runtime: AdapterRuntime; // { sessionId, sessionParams, sessionDisplayId, taskKey }
config: Record<string, unknown>; // The agent's adapterConfig blob
context: Record<string, unknown>; // Runtime context (taskId, wakeReason, approvalId, etc.)
onLog: (stream: "stdout" | "stderr", chunk: string) => Promise<void>;
onMeta?: (meta: AdapterInvocationMeta) => Promise<void>;
authToken?: string;
}
interface AdapterExecutionResult {
exitCode: number | null;
signal: string | null;
timedOut: boolean;
errorMessage?: string | null;
usage?: UsageSummary; // { inputTokens, outputTokens, cachedInputTokens? }
sessionId?: string | null; // Legacy — prefer sessionParams
sessionParams?: Record<string, unknown> | null; // Opaque session state persisted between runs
sessionDisplayId?: string | null;
provider?: string | null; // "anthropic", "openai", etc.
model?: string | null;
costUsd?: number | null;
resultJson?: Record<string, unknown> | null;
summary?: string | null; // Human-readable summary of what the agent did
clearSession?: boolean; // true = tell Paperclip to forget the stored session
}
interface AdapterSessionCodec {
deserialize(raw: unknown): Record<string, unknown> | null;
serialize(params: Record<string, unknown> | null): Record<string, unknown> | null;
getDisplayId?(params: Record<string, unknown> | null): string | null;
}
Module Interfaces
// Server — registered in server/src/adapters/registry.ts
interface ServerAdapterModule {
type: string;
execute(ctx: AdapterExecutionContext): Promise<AdapterExecutionResult>;
testEnvironment(ctx: AdapterEnvironmentTestContext): Promise<AdapterEnvironmentTestResult>;
sessionCodec?: AdapterSessionCodec;
supportsLocalAgentJwt?: boolean;
models?: { id: string; label: string }[];
agentConfigurationDoc?: string;
}
// UI — registered in ui/src/adapters/registry.ts
interface UIAdapterModule {
type: string;
label: string;
parseStdoutLine: (line: string, ts: string) => TranscriptEntry[];
ConfigFields: ComponentType<AdapterConfigFieldsProps>;
buildAdapterConfig: (values: CreateConfigValues) => Record<string, unknown>;
}
// CLI — registered in cli/src/adapters/registry.ts
interface CLIAdapterModule {
type: string;
formatStdoutEvent: (line: string, debug: boolean) => void;
}
2.1 Adapter Environment Test Contract
Every server adapter must implement testEnvironment(...). This powers the board UI "Test environment" button in agent configuration.
type AdapterEnvironmentCheckLevel = "info" | "warn" | "error";
type AdapterEnvironmentTestStatus = "pass" | "warn" | "fail";
interface AdapterEnvironmentCheck {
code: string;
level: AdapterEnvironmentCheckLevel;
message: string;
detail?: string | null;
hint?: string | null;
}
interface AdapterEnvironmentTestResult {
adapterType: string;
status: AdapterEnvironmentTestStatus;
checks: AdapterEnvironmentCheck[];
testedAt: string; // ISO timestamp
}
interface AdapterEnvironmentTestContext {
companyId: string;
adapterType: string;
config: Record<string, unknown>; // runtime-resolved adapterConfig
}
Guidelines:
- Return structured diagnostics, never throw for expected findings.
- Use
errorfor invalid/unusable runtime setup (bad cwd, missing command, invalid URL). - Use
warnfor non-blocking but important situations. - Use
infofor successful checks and context.
Severity policy is product-critical: warnings are not save blockers.
Example: for claude_local, an explicitly configured ANTHROPIC_API_KEY or selected managed API connection is info: the user chose that authentication. An ambient server key overriding subscription login remains warn, not error.
3. Step-by-Step: Creating a New Adapter
3.1 Create the Package
packages/adapters/<name>/
package.json
tsconfig.json
src/
index.ts
server/index.ts
server/execute.ts
server/parse.ts
ui/index.ts
ui/parse-stdout.ts
ui/build-config.ts
cli/index.ts
cli/format-event.ts
package.json — must use the four-export convention:
{
"name": "@paperclipai/adapter-<name>",
"version": "0.0.1",
"private": true,
"type": "module",
"exports": {
".": "./src/index.ts",
"./server": "./src/server/index.ts",
"./ui": "./src/ui/index.ts",
"./cli": "./src/cli/index.ts"
},
"dependencies": {
"@paperclipai/adapter-utils": "workspace:*",
"picocolors": "^1.1.1"
},
"devDependencies": {
"typescript": "^5.7.3"
}
}
3.2 Root index.ts — Adapter Metadata
This file is imported by all three consumers (server, UI, CLI). Keep it dependency-free (no Node APIs, no React).
export const type = "my_agent"; // snake_case, globally unique
export const label = "My Agent (local)";
export const models = [
{ id: "model-a", label: "Model A" },
{ id: "model-b", label: "Model B" },
];
export const agentConfigurationDoc = `# my_agent agent configuration
...document all config fields here...
`;
Required exports:
type— the adapter type key, stored inagents.adapter_typelabel— human-readable name for the UImodels— available model options for the agent creation formagentConfigurationDoc— markdown describing alladapterConfigfields (used by LLM agents configuring other agents)
Writing agentConfigurationDoc as routing logic:
The agentConfigurationDoc is read by LLM agents (including Paperclip agents that create other agents). Write it as routing logic, not marketing copy. Include concrete "use when" and "don't use when" guidance so an LLM can decide whether this adapter is appropriate for a given task.
export const agentConfigurationDoc = `# my_agent agent configuration
Adapter: my_agent
Use when:
- The agent needs to run MyAgent CLI locally on the host machine
- You need session persistence across runs (MyAgent supports thread resumption)
- The task requires MyAgent-specific tools (e.g. web search, code execution)
Don't use when:
- You need a simple one-shot script execution (use the "process" adapter instead)
- The agent doesn't need conversational context between runs (process adapter is simpler)
- MyAgent CLI is not installed on the host
Core fields:
- cwd (string, required): absolute working directory for the agent process
...
`;
Adding explicit negative cases improves adapter selection accuracy. One concrete anti-pattern is worth more than three paragraphs of description.
3.3 Server Module
server/execute.ts — The Core
This is the most important file. It receives an AdapterExecutionContext and must return an AdapterExecutionResult.
Required behavior:
- Read config — extract typed values from
ctx.configusing helpers (asString,asNumber,asBoolean,asStringArray,parseObjectfrom@paperclipai/adapter-utils/server-utils) - Build environment — call
buildPaperclipEnv(agent)then layer inPAPERCLIP_RUN_ID, context vars (PAPERCLIP_TASK_ID,PAPERCLIP_WAKE_REASON,PAPERCLIP_WAKE_COMMENT_ID,PAPERCLIP_APPROVAL_ID,PAPERCLIP_APPROVAL_STATUS,PAPERCLIP_LINKED_ISSUE_IDS), user env overrides, and auth token - Resolve session — check
runtime.sessionParams/runtime.sessionIdfor an existing session; validate it's compatible (e.g. same cwd); decide whether to resume or start fresh - Render prompt — use
renderTemplate(template, data)with the template variables:agentId,companyId,runId,company,agent,run,context - Call onMeta — emit adapter invocation metadata before spawning the process
- Spawn the process — use
runChildProcess()for CLI-based agents orfetch()for HTTP-based agents - Parse output — convert the agent's stdout into structured data (session id, usage, summary, errors)
- Handle session errors — if resume fails with "unknown session", retry with a fresh session and set
clearSession: true - Return AdapterExecutionResult — populate all fields the agent runtime supports
Environment variables the server always injects:
server/parse.ts — Output Parser
Parse the agent's stdout format into structured data. Must handle:
- Session identification — extract session/thread ID from init events
- Usage tracking — extract token counts (input, output, cached)
- Cost tracking — extract cost if available
- Summary extraction — pull the agent's final text response
- Error detection — identify error states, extract error messages
- Unknown session detection — export an
is<Agent>UnknownSessionError()function for retry logic
Treat agent output as untrusted. The stdout you're parsing comes from an LLM-driven process that may have executed arbitrary tool calls, fetched external content, or been influenced by prompt injection in the files it read. Parse defensively:
- Never
eval()or dynamically execute anything from output - Use safe extraction helpers (
asString,asNumber,parseJson) — they return fallbacks on unexpected types - Validate session IDs and other structured data before passing them through
- If output contains URLs, file paths, or commands, do not act on them in the adapter — just record them
server/index.ts — Server Exports
export { execute } from "./execute.js";
export { testEnvironment } from "./test.js";
export { parseMyAgentOutput, isMyAgentUnknownSessionError } from "./parse.js";
// Session codec — required for session persistence
export const sessionCodec: AdapterSessionCodec = {
deserialize(raw) { /* raw DB JSON -> typed params or null */ },
serialize(params) { /* typed params -> JSON for DB storage */ },
getDisplayId(params) { /* -> human-readable session id string */ },
};
server/test.ts — Environment Diagnostics
Implement adapter-specific preflight checks used by the UI test button.
Minimum expectations:
- Validate required config primitives (paths, commands, URLs, auth assumptions)
- Return check objects with deterministic
codevalues - Map severity consistently (
info/warn/error) - Compute final status:
failif anyerrorwarnif no errors and at least one warningpassotherwise
This operation should be lightweight and side-effect free.
3.4 UI Module
ui/parse-stdout.ts — Transcript Parser
Converts individual stdout lines into TranscriptEntry[] for the run detail viewer. Must handle the agent's streaming output format and produce entries of these kinds:
init— model/session initializationassistant— agent text responsesthinking— agent thinking/reasoning (if supported)tool_call— tool invocations with name and inputtool_result— tool results with content and error flaguser— user messages in the conversationresult— final result with usage statsstdout— fallback for unparseable lines
export function parseMyAgentStdoutLine(line: string, ts: string): TranscriptEntry[] {
// Parse JSON line, map to appropriate TranscriptEntry kind(s)
// Return [{ kind: "stdout", ts, text: line }] as fallback
}
ui/build-config.ts — Config Builder
Converts the UI form's CreateConfigValues into the adapterConfig JSON blob stored on the agent.
export function buildMyAgentConfig(v: CreateConfigValues): Record<string, unknown> {
const ac: Record<string, unknown> = {};
if (v.cwd) ac.cwd = v.cwd;
if (v.promptTemplate) ac.promptTemplate = v.promptTemplate;
if (v.model) ac.model = v.model;
ac.timeoutSec = 0;
ac.graceSec = 15;
// ... adapter-specific fields
return ac;
}
UI Config Fields Component
Create ui/src/adapters/<name>/config-fields.tsx with a React component implementing AdapterConfigFieldsProps. This renders adapter-specific form fields in the agent creation/edit form.
Use the shared primitives from ui/src/components/agent-config-primitives:
Field— labeled form field wrapperToggleField— boolean toggle with label and hintDraftInput— text input with draft/commit behaviorDraftNumberInput— number input with draft/commit behaviorhelp— standard hint text for common fields
The component must support both create mode (using values/set) and edit mode (using config/eff/mark).
3.5 CLI Module
cli/format-event.ts — Terminal Formatter
Pretty-prints stdout lines for paperclipai run --watch. Use picocolors for coloring.
import pc from "picocolors";
export function printMyAgentStreamEvent(raw: string, debug: boolean): void {
// Parse JSON line from agent stdout
// Print colored output: blue for system, green for assistant, yellow for tools
// In debug mode, print unrecognized lines in gray
}
4. Registration Checklist
After creating the adapter package, register it in all three consumers:
4.1 Server Registry (server/src/adapters/registry.ts)
import { execute as myExecute, sessionCodec as mySessionCodec } from "@paperclipai/adapter-my-agent/server";
import { agentConfigurationDoc as myDoc, models as myModels } from "@paperclipai/adapter-my-agent";
const myAgentAdapter: ServerAdapterModule = {
type: "my_agent",
execute: myExecute,
sessionCodec: mySessionCodec,
models: myModels,
supportsLocalAgentJwt: true, // true if agent can use Paperclip API
agentConfigurationDoc: myDoc,
};
// Add to the adaptersByType map
const adaptersByType = new Map<string, ServerAdapterModule>(
[..., myAgentAdapter].map((a) => [a.type, a]),
);
4.2 UI Registry (ui/src/adapters/registry.ts)
import { myAgentUIAdapter } from "./my-agent";
const adaptersByType = new Map<string, UIAdapterModule>(
[..., myAgentUIAdapter].map((a) => [a.type, a]),
);
With ui/src/adapters/my-agent/index.ts:
import type { UIAdapterModule } from "../types";
import { parseMyAgentStdoutLine } from "@paperclipai/adapter-my-agent/ui";
import { MyAgentConfigFields } from "./config-fields";
import { buildMyAgentConfig } from "@paperclipai/adapter-my-agent/ui";
export const myAgentUIAdapter: UIAdapterModule = {
type: "my_agent",
label: "My Agent",
parseStdoutLine: parseMyAgentStdoutLine,
ConfigFields: MyAgentConfigFields,
buildAdapterConfig: buildMyAgentConfig,
};
4.3 CLI Registry (cli/src/adapters/registry.ts)
import { printMyAgentStreamEvent } from "@paperclipai/adapter-my-agent/cli";
const myAgentCLIAdapter: CLIAdapterModule = {
type: "my_agent",
formatStdoutEvent: printMyAgentStreamEvent,
};
// Add to the adaptersByType map
5. Session Management — Designing for Long Runs
Sessions allow agents to maintain conversation context across runs. The system is codec-based — each adapter defines how to serialize/deserialize its session state.
Design for long runs from the start. Treat session reuse as the default primitive, not an optimization to add later. An agent working on an issue may be woken dozens of times — for the initial assignment, approval callbacks, re-assignments, manual nudges. Each wake should resume the existing conversation so the agent retains full context about what it has already done, what files it has read, and what decisions it has made. Starting fresh each time wastes tokens on re-reading the same files and risks contradictory decisions.
Key concepts:
sessionParamsis an opaqueRecord<string, unknown>stored in the DB per task- The adapter's
sessionCodec.serialize()converts execution result data to storable params sessionCodec.deserialize()converts stored params back for the next runsessionCodec.getDisplayId()extracts a human-readable session ID for the UI- cwd-aware resume: if the session was created in a different cwd than the current config, skip resuming (prevents cross-project session contamination)
- Unknown session retry: if resume fails with a "session not found" error, retry with a fresh session and return
clearSession: trueso Paperclip wipes the stale session
If the agent runtime supports any form of context compaction or conversation compression (e.g. Claude Code's automatic context management, or Codex's previous_response_id chaining), lean on it. Adapters that support session resume get compaction for free — the agent runtime handles context window management internally across resumes.
Pattern (from both claude-local and codex-local):
const canResumeSession =
runtimeSessionId.length > 0 &&
(runtimeSessionCwd.length === 0 || path.resolve(runtimeSessionCwd) === path.resolve(cwd));
const sessionId = canResumeSession ? runtimeSessionId : null;
// ... run attempt ...
// If resume failed with unknown session, retry fresh
if (sessionId && !proc.timedOut && exitCode !== 0 && isUnknownSessionError(output)) {
const retry = await runAttempt(null);
return toResult(retry, { clearSessionOnMissingSession: true });
}
6. Server-Utils Helpers
Import from @paperclipai/adapter-utils/server-utils:
7. Conventions and Patterns
Naming
- Adapter type:
snake_case(e.g.claude_local,codex_local) - Package name:
@paperclipai/adapter-<kebab-name> - Package directory:
packages/adapters/<kebab-name>/
Config Parsing
- Never trust
configvalues directly — always useasString,asNumber, etc. - Provide sensible defaults for every optional field
- Document all fields in
agentConfigurationDoc
Prompt Templates
- Support
promptTemplatefor every run - Use
renderTemplate()with the standard variable set - Default prompt should use
DEFAULT_PAPERCLIP_AGENT_PROMPT_TEMPLATEfrom@paperclipai/adapter-utils/server-utilsso local adapters share Paperclip's execution contract: act in the same heartbeat, avoid planning-only exits unless requested, leave durable progress and a next action, use child issues instead of polling, mark blockers with owner/action, and respect governance boundaries.
Error Handling
- Differentiate timeout vs process error vs parse failure
- Always populate
errorMessageon failure - Include raw stdout/stderr in
resultJsonwhen parsing fails - Handle the agent CLI not being installed (command not found)
Logging
- Call
onLog("stdout", ...)andonLog("stderr", ...)for all process output — this feeds the real-time run viewer - Call
onMeta(...)before spawning to record invocation details - Use
redactEnvForLogs()when including env in meta
Paperclip Skills Injection
Paperclip ships shared skills (in the repo's top-level skills/ directory) that agents need at runtime — things like the paperclip API skill and the paperclip-create-agent workflow skill. Each adapter is responsible for making these skills discoverable by its agent runtime without polluting the agent's working directory.
The constraint: never copy or symlink skills into the agent's cwd. The cwd is the user's project checkout — writing .claude/skills/ or any other files into it would contaminate the repo with Paperclip internals, break git status, and potentially leak into commits.
The pattern: create a clean, isolated location for skills and tell the agent runtime to look there.
How claude-local does it:
- At execution time, create a fresh tmpdir:
mkdtemp("paperclip-skills-") - Inside it, create
.claude/skills/(the directory structure Claude Code expects) - Symlink each skill directory from the repo's
skills/into the tmpdir's.claude/skills/ - Pass the tmpdir to Claude Code via
--add-dir <tmpdir>— this makes Claude Code discover the skills as if they were registered in that directory, without touching the agent's actual cwd - Clean up the tmpdir in a
finallyblock after the run completes
// From claude-local execute.ts
async function buildSkillsDir(): Promise<string> {
const tmp = await fs.mkdtemp(path.join(os.tmpdir(), "paperclip-skills-"));
const target = path.join(tmp, ".claude", "skills");
await fs.mkdir(target, { recursive: true });
const entries = await fs.readdir(PAPERCLIP_SKILLS_DIR, { withFileTypes: true });
for (const entry of entries) {
if (entry.isDirectory()) {
await fs.symlink(
path.join(PAPERCLIP_SKILLS_DIR, entry.name),
path.join(target, entry.name),
);
}
}
return tmp;
}
// In execute(): pass --add-dir to Claude Code
const skillsDir = await buildSkillsDir();
args.push("--add-dir", skillsDir);
// ... run process ...
// In finally: fs.rm(skillsDir, { recursive: true, force: true })
How codex-local does it:
Codex has a global personal skills directory ($CODEX_HOME/skills or ~/.codex/skills). The adapter symlinks Paperclip skills there if they don't already exist. This is acceptable because it's the agent tool's own config directory, not the user's project.
// From codex-local execute.ts
async function ensureCodexSkillsInjected(onLog) {
const skillsHome = path.join(codexHomeDir(), "skills");
await fs.mkdir(skillsHome, { recursive: true });
for (const entry of entries) {
const target = path.join(skillsHome, entry.name);
const existing = await fs.lstat(target).catch(() => null);
if (existing) continue; // Don't overwrite user's own skills
await fs.symlink(source, target);
}
}
For a new adapter: figure out how your agent runtime discovers skills/plugins, then choose the cleanest injection path:
- Best: tmpdir + flag (like claude-local) — if the runtime supports an "additional directory" flag, create a tmpdir, symlink skills in, pass the flag, clean up after. Zero side effects.
- Acceptable: global config dir (like codex-local) — if the runtime has a global skills/plugins directory separate from the project, symlink there. Skip existing entries to avoid overwriting user customizations.
- Acceptable: env var — if the runtime reads a skills/plugin path from an environment variable, point it at the repo's
skills/directory directly. - Last resort: prompt injection — if the runtime has no plugin system, include skill content in the prompt template itself. This uses tokens but avoids filesystem side effects entirely.
Skills as loaded procedures, not prompt bloat. The Paperclip skills (like paperclip and paperclip-create-agent) are designed as on-demand procedures: the agent sees skill metadata (name + description) in its context, but only loads the full SKILL.md content when it decides to invoke a skill. This keeps the base prompt small. When writing agentConfigurationDoc or prompt templates for your adapter, do not inline skill content — let the agent runtime's skill discovery do the work. The descriptions in each SKILL.md frontmatter act as routing logic: they tell the agent when to load the full skill, not what the skill contains.
Explicit vs. fuzzy skill invocation. For production workflows where reliability matters (e.g. an agent that must always call the Paperclip API to report status), use explicit instructions in the prompt template: "Use the paperclip skill to report your progress." Fuzzy routing (letting the model decide based on description matching) is fine for exploratory tasks but unreliable for mandatory procedures.
8. Security Considerations
Adapters sit at the boundary between Paperclip's orchestration layer and arbitrary agent execution. This is a high-risk surface.
Treat Agent Output as Untrusted
The agent process runs LLM-driven code that reads external files, fetches URLs, and executes tools. Its output may be influenced by prompt injection from the content it processes. The adapter's parse layer is a trust boundary — validate everything, execute nothing.
Secret Injection via Environment, Not Prompts
Never put secrets (API keys, tokens) into prompt templates or config fields that flow through the LLM. Instead, inject them as environment variables that the agent's tools can read directly:
PAPERCLIP_API_KEYis injected by the server into the process environment, not the prompt- User-provided secrets in
config.envare passed as env vars, redacted inonMetalogs - The
redactEnvForLogs()helper automatically masks any key matching/(key|token|secret|password|authorization|cookie)/i
This follows the "sidecar injection" pattern: the model never sees the real secret value, but the tools it invokes can read it from the environment.
Network Access
If your agent runtime supports network access controls (sandboxing, allowlists), configure them in the adapter:
- Prefer minimal allowlists over open internet access. An agent that only needs to call the Paperclip API and GitHub should not have access to arbitrary hosts.
- Skills + network = amplified risk. A skill that teaches the agent to make HTTP requests combined with unrestricted network access creates an exfiltration path. Constrain one or the other.
- If the runtime supports layered policies (org-level defaults + per-request overrides), wire the org-level policy into the adapter config and let per-agent config narrow further.
Process Isolation
- CLI-based adapters inherit the server's user permissions. The
cwdandenvconfig determine what the agent process can access on the filesystem. dangerouslySkipPermissions/dangerouslyBypassApprovalsAndSandboxflags exist for development convenience but must be documented as dangerous inagentConfigurationDoc. Production deployments should not use them.- Timeout and grace period (
timeoutSec,graceSec) are safety rails — always enforce them. A runaway agent process without a timeout can consume unbounded resources.
9. TranscriptEntry Kinds Reference
The UI run viewer displays these entry kinds:
10. Testing
Create tests in server/src/__tests__/<adapter-name>-adapter.test.ts. Test:
- Output parsing — feed sample stdout through your parser, verify structured output
- Unknown session detection — verify the
is<Agent>UnknownSessionErrorfunction - Config building — verify
buildConfigproduces correct adapterConfig from form values - Session codec — verify serialize/deserialize round-trips
11. Minimal Adapter Checklist
-
packages/adapters/<name>/package.jsonwith four exports (.,./server,./ui,./cli) - Root
index.tswithtype,label,models,agentConfigurationDoc -
server/execute.tsimplementingAdapterExecutionContext -> AdapterExecutionResult -
server/test.tsimplementingAdapterEnvironmentTestContext -> AdapterEnvironmentTestResult -
server/parse.tswith output parser and unknown-session detector -
server/index.tsexportingexecute,testEnvironment,sessionCodec, parse helpers -
ui/parse-stdout.tswithStdoutLineParserfor the run viewer -
ui/build-config.tswithCreateConfigValues -> adapterConfigbuilder -
ui/src/adapters/<name>/config-fields.tsxReact component for agent form -
ui/src/adapters/<name>/index.tsassembling theUIAdapterModule -
cli/format-event.tswith terminal formatter -
cli/index.tsexporting the formatter - Registered in
server/src/adapters/registry.ts - Registered in
ui/src/adapters/registry.ts - Registered in
cli/src/adapters/registry.ts - Added to workspace in root (if not already covered by glob)