🥞 fln
A local, explainable context compiler for AI coding agents. Retrieval without embeddings. Context without a server.
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fln analyzes your codebase, plans what to include, and emits a single AI-ready file — with diagnostics that explain every decision. Think tsc for LLM context: analyze → plan → emit, all local.
npx fln # or: npm i -g fln · bunx fln · brew install nesvet/tap/fln
fln # → my-app-1.2.0.md in the current directory
$ fln --no-ansi
✓ my-app-1.2.0.md (42 files, 12_840 tokens)
One markdown file — header, directory tree, backtick-safe fences. Paste into Claude, ChatGPT, Gemini, Grok, Cursor, or Copilot; pipe to a CLI LLM (fln --stdout | llm "..."); or serve over MCP.
# Codebase Snapshot: demo-app
Generated: 2026-07-06 17:30
Files: 6 | Directories: 3
---
## Directory Tree
```text
├── README.md
├── package.json
├── src
│ ├── index.ts
│ ├── helper.ts
│ └── utils.ts
└── tests
└── index.test.ts
```
---
## Source Files
### src/index.ts
```ts
import { helper } from "./helper";
import { format } from "./utils";
export function main(): string {
return format(helper());
}
```
--relevant) without embeddingsIf you use LLMs on real projects, you've hit these limits:
fln treats codebase context the way tsc treats TypeScript: analyze, plan, emit — with diagnostics (why, doctor, plan, diff) and MCP.
JIT agent retrieval (tool calls, embeddings, live search) is great for interactive exploration. fln is the complementary AOT snapshot compiler: it builds a deterministic context spine before the agent starts — structure-based retrieval (imports, priority, token budgets), no embeddings, no server. Same input → same snapshot; CI-friendly; offline.
why/doctor/plan/diff, --relevant, --stdin--compress, watch mode, web UIhub→ingest URL trick@codebase — live IDE retrieval on large reposNot mutually exclusive: fln and repomix both produce paste-ready files; fln adds the compiler/diagnostics layer.
fln plan assigns fidelity per file and projects tokens before you spend the budget. With --relevant, only the import-graph neighborhood of the seed is included:
$ fln plan --relevant src/cli/index.ts --budget 200000
# Context Plan: .
Budget: 200,000 tokens
Projected: 67,149 tokens
Files included: 100
Files omitted: 1
## Included files
src/api/index.ts — ~239 tokens (entry point — high priority)
src/cli/index.ts — ~89 tokens (seed file)
src/cli/output/index.ts — ~28 tokens (entry point — high priority)
...
Full output: assets/demo-plan.md. Use --format json for CI/agents. Formal schema: schema/fln-plan.json ($id: https://fln.nesvet.dev/schema/plan).
fln plan --budget 200000
fln plan --relevant src/cli/index.ts --budget 200000
fln plan --format json
fln why .env # why is .env excluded?
fln why src/index.ts # why is index.ts included?
fln why .env --format json # machine-readable for CI/agents
fln doctor . # config, git, scan stats, token estimate
fln doctor --max-tokens 200000 # warn if over budget
fln doctor --format json --recommend-budget 200000
fln mcp # stdio MCP server
fln mcp --http --port 3000 # Streamable HTTP
fln why is a first-class path-decision CLI with stable reasons (gitignore, security, size, whitelist, …) and JSON for agents.
Resources: fln_file://{path}, fln_snapshot://{name}.
{
"mcpServers": {
"fln": { "command": "fln", "args": ["mcp"] }
}
}
--stdin force-includes piped paths (like -i), then prunes the tree to exactly that set. Security still applies — detected secrets are never embedded:
git ls-files | fln --stdin -o snapshot.md
git ls-files --others | fln --stdin -o untracked.md
git diff --name-only HEAD~1 | fln --stdin --stdout
rg -l TODO | fln --stdin --stdout
git diff --name-only main | fln plan --stdin --budget 50000
fln --copy # clipboard (32 MiB default; FLN_COPY_MAX_BYTES to override)
fln --stdout | llm "What are the biggest architecture issues here?"
fln --stdout | pbcopy # fallback when --copy isn't available
fln --since main --ext ts,tsx
fln --since main --diff-hunks
fln --relevant src/index.ts --outline
fln --banner-file .prompt.md
fln --banner "Review this codebase for security vulnerabilities."
Performance: linux-x64 CI baselines for the medium fixture (5000 files) — dry-run ~1.1s, full flatten ~2.4s (median; gate = baseline +10%). Details: benchmarks/README.md.
.gitignore; skips binaries/lockfiles; configurable size limitsvendor/ deprioritized)--verbose extension breakdown; self-aware (skips prior fln output)package.json, Cargo.toml, pyproject.toml, pom.xml, go.mod, …md / json; --compress / --outline (custom line-based signatures, not Tree-sitter)--max-total-size graceful omit; --strict-limits for CI; doctor --recommend-budget--strict-toctou); --annotate-tree; --collect-todo (same content pass)--dry-run; namespace API: fln(), .inspect(), .explain(), .doctor(), .plan(), .diff(), .mcp()omittedFiles in JSON (flat, capped, all reasons)flatten, why, doctor, plan, diff, mcp). fln upgrade is the explicit exception.~/.config/fln/usage.json may store runCount / lastRun only (sponsor message on runs 5 and 25). Hide: FLN_NO_SPONSOR=1 or --no-sponsor-message. Skip write: --no-local-state.npx fln # run once
bunx fln
npm install -g fln
bun add -g fln
# Native binary — no Node required
curl -fsSL https://fln.nesvet.dev/install | sh
powershell -c "irm fln.nesvet.dev/install.ps1 | iex"
brew install nesvet/tap/fln
# Homebrew 6.0+: trust the formula on first use
brew trust --formula nesvet/tap/fln
fln upgrade # binary self-update (sha256 + optional cosign)
Pin version / custom dir (macOS/Linux):
curl -fsSL https://fln.nesvet.dev/install | FLN_VERSION="<version>" INSTALL_DIR="$HOME/.local/bin" sh
Windows:
$env:FLN_VERSION = "<version>"
$env:INSTALL_DIR = "$env:LOCALAPPDATA\fln\bin"
powershell -c "irm fln.nesvet.dev/install.ps1 | iex"
Manual GitHub Release:
curl -L "https://github.com/nesvet/fln/releases/latest/download/fln-macos-x64.tar.gz" | tar -xz -C /usr/local/bin
chmod +x /usr/local/bin/fln
Completions (bash / zsh / fish / PowerShell) — from a clone: source completions/_fln (zsh), source completions/fln.bash, etc. After npm i -g fln: source "$(npm root -g)/fln/completions/_fln". Regenerate: bun run generate:completions.
fln [directory] [...flags]
fln init [--overwrite]
fln why <path> [directory] [...flags]
fln doctor [directory] [...flags]
fln plan [directory] [--budget <n>] [--relevant <seed>] [...flags]
fln diff <before> <after> [...flags]
fln diff --since <ref>
fln mcp [directory]
fln upgrade
fln # → my-app-1.2.0.md
fln . -o context.md
fln src -o . # scan src/, write to project root
fln -e "*.test.ts" -e "fixtures/"
fln -e "*.md" -e '!README.md'
fln --ext ts,tsx --since HEAD~1
fln -i "src/generated/schema.ts" # force-include gitignored file
fln --only "**/*.ts"
fln why .env --include-hidden
fln --dry-run --verbose
fln --format json -o snapshot.json
fln mcp
Files over --max-file-size are skipped unless force-included (-i / --stdin); content streams at render. See SECURITY.md.
Canonical list: fln --help. Config: fln.json / schema/fln.json. API: below.
Multi-word flags accept camelCase aliases (e.g. --maxFileSize, --noTree) — docs use kebab-case.
Subcommands
Output
Filtering
Content
Doctor: --recommend-budget <n>. MCP: --http, --port <n> (default 3000).
Logging: -q / -V / --debug / --no-ansi / --no-sponsor-message / --no-local-state / -v / -h.
Quote globs:
"*.test.ts". Un-exclude:-e "*.md" -e '!README.md'.
fln init
Writes fln.json with JSON Schema IntelliSense ($schema: https://fln.nesvet.dev/schema).
{
"$schema": "https://fln.nesvet.dev/schema",
"output": "output.md",
"exclude": [],
"include": [],
"only": [],
"includeHidden": false,
"maxFileSize": "10mb",
"maxTotalSize": "0",
"maxTokens": 0,
"maxContentTokens": 0,
"tokenModel": "estimate",
"strictLimits": false,
"encoding": "auto",
"format": "md",
"followSymlinks": false,
"overwrite": false
}
Additional keys (gitignore, banner, securityPatterns, …): schema/fln.json and API. Patterns are gitignore-style relative to input; CLI merges with the file (--ignore-config skips it).
Fresh codebase.md on every push — download anytime to chat about the exact state of main or a PR:
# .github/workflows/codebase-snapshot.yaml
name: Snapshot Codebase
on:
push:
branches: ["main"]
pull_request:
jobs:
snapshot:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v7
- name: Generate snapshot
run: npx fln . -o codebase.md -w --no-ansi
- uses: actions/upload-artifact@v7
with:
name: codebase-snapshot
path: codebase.md
retention-days: 7
Pre-commit budget guard:
# .husky/pre-commit
npx fln . --dry-run --max-total-size 5mb
npm install fln
import { fln } from "fln";
const result = await fln({
input: "./src",
output: "snapshot.md",
exclude: ["*.test.ts", "fixtures/"],
onProgress: (current, total) => {
process.stdout.write(`\r${current}/${total} files`);
},
});
console.log(`${result.filesIncluded} files → ${result.outputPath}`);
console.log(`~${result.outputTokenCount.toLocaleString()} tokens`);
const { root, stats } = await fln.inspect({ input: "./src", dryRun: true });
const decision = await fln.explain({ path: ".env", input: "./src" });
const report = await fln.doctor({ input: "./src" });
const planResult = await fln.plan({
input: "./src",
budget: 200_000,
relevant: ["src/index.ts"],
});
const diffResult = await fln.diff({ before: "snapshot-v1.md", after: "snapshot-v2.md" });
await fln.mcp({ defaultInput: "./src" });
Formal schemas for JSON: plan ($id: https://fln.nesvet.dev/schema/plan), diff ($id: https://fln.nesvet.dev/schema/diff).
Matches FlnOptions / FlnResult / FlnInspectResult / FlnMcpOptions in the package types.
Options (FlnOptions)
MCP options (FlnMcpOptions)
Config file logLevel default in schema/fln.json is "normal" when using fln.json alone.
Diagnostics: fln why <path> from the CLI (--format json for agents/CI; not in fln.json). SDK: fln.explain().
fln doctor [directory] runs a dry-run scan (metadata only, no flatten file). Same filtering flags as flatten (-e, -i, --only, --since, --ext, --stdin, …).
Human output includes config path, git branch/dirty, file counts, estimated size/tokens (±20% vs real flatten), top extensions, and warnings (oversized files, security paths in tree, --max-tokens budget). With --since and no matching changes, prints the same early message as fln and exits 0.
fln doctor .
fln doctor --format json --max-tokens 500000
fln doctor --format json --recommend-budget 200000
JSON shape: schemaVersion: 1, config (loaded, path, optional ignored when --ignore-config), git, scan, estimate, extensions, warnings, optional recommend (exclude, projectedTokens, omittedCount). Formal schema: schema/fln-doctor.json ($id: https://fln.nesvet.dev/schema/doctor).
import { fln, toFlnWhyJson } from "fln";
const report = await fln.doctor({
input: projectDir,
recommendBudget: 200_000,
});
const decision = await fln.explain({ path: ".env", input: projectDir });
// why CLI JSON: { schemaVersion: 1, input: "<abs dir>", decision: { relativePath, included, reason, detail? } }
fln.doctor() does not accept --no-local-state or --no-sponsor-message — those are CLI-only. Programmatic sponsor status reflects usage.json and FLN_NO_SPONSOR only.
--format json emits a structured document. Top-level root is the FileNode tree; options.tree / options.contents are the boolean flags used for that run. The files array is omitted when --no-contents is set.
Formal schema: schema/fln-output.json ($id: https://fln.nesvet.dev/schema/output).
fln --format json --max-tokens 200000 -o snap.json
jq '.omittedFiles[] | select(.reason=="tokenLimit") | .path' snap.json
With fln why --format json, errors use toFlnFailureJson on stderr ({ ok: false, error: { code, message, hint? } }).
Inspect (fln.inspect) — same options as fln(), scan only. Returns FlnInspectResult: projectName, root (FileNode with skipReason), stats.
Programmatic API surface: operations on the namespace only — fln(), fln.inspect(), fln.explain(), fln.doctor(), fln.plan(), fln.diff(), fln.mcp(). Standalone: VERSION, toFlnWhyJson, toFlnDoctorJson, toFlnPlanJson, toFlnDiffJson, toFlnFailureJson, formatPlanText, formatDoctorText, formatDiffText, FlnError, and types.
Result (FlnResult): projectName, filesIncluded, filesScanned, directories, binary, skipped, errors, totalSizeBytes, outputSizeBytes, outputTokenCount, outputPath ("-" for stdout, "" when dryRun or copy).
Error codes (FlnError)
import { fln, FlnError } from "fln";
try {
await fln({ input: dir });
} catch (error) {
if (error instanceof FlnError)
console.error(error.code, error.hint ?? error.message);
throw error;
}
How is fln different from repomix?
Both produce a paste-ready file. repomix is a feature-rich packer (remote repos, Tree-sitter compression, watch mode). fln is a compiler with diagnostics — why, doctor, plan, diff, --relevant, and an MCP server. Pick repomix for one-shot web-chat paste or remote repos; pick fln when you need reproducibility, CI guards, or explainability. See Compare.
Do I need embeddings or a server?
No. fln is fully local — zero network during a normal run. --relevant walks the import graph with a zero-dependency line-based parser (TS/JS/Py/Go/Rust/Java/C) — structure-based retrieval, not similarity search.
Does it work with MCP agents?
Yes. fln mcp starts an MCP server (stdio by default; --http --port for Streamable HTTP) exposing fln_snapshot, fln_plan, fln_diff, fln_why, and fln_doctor to any MCP-aware agent (Claude Code, Cursor, Codex CLI, VS Code). See Workflows.
Is it safe to pipe secrets?
Detected secrets are never embedded, even with force-include. fln skips sensitive paths (.env, keys, credentials) by pattern, and runs entropy + known-secret detection (AWS, Google, GitHub, Stripe, Slack, Azure, GitLab, JWT, PEM) on file headers. A force-included secret file stays in the tree with skipReason: "security" — content is omitted. Detection is not a guarantee — review output before sharing. See SECURITY.md.
Does --stdin bypass .gitignore?
Yes — intentionally. --stdin force-includes the piped paths (bypassing .gitignore, exclude, and hidden filters, like -i), then prunes the tree to exactly that set. That is what makes git ls-files --others | fln --stdin work for untracked files. Security patterns still apply; paths resolving outside the input directory are dropped.
Why AOT instead of JIT retrieval?
They solve different problems. JIT (Cursor @codebase, agentic search) is great for interactive exploration on large repos. AOT (fln) is great for reproducible snapshots, CI context guards, budget planning, and offline workflows — and for explainability. You decide what to include before the agent starts. They're complementary; many stacks use both.
How do I update fln?
npm install -g fln or bun add -g flnbrew upgrade nesvet/tap/flncurl …/install): fln upgrade — downloads the latest GitHub Release, verifies sha256 (required), optionally verifies cosign when cosign is on PATH.--token-model controls how fln estimates token counts for budgets, doctor, and diff deltas.
Use gpt-4o or gpt-5 when targeting OpenAI models. Use estimate for quick checks. Markdown snapshots record the model in the header; fln diff uses it for token deltas.
Real outputs from examples/:
Node.js — requires >=22.0.0, ESM-only ("type": "module"). Install via npm i -g fln or run with npx.
Bun — requires >=1.4.0. Install via bun add -g fln or run with bunx.
Standalone binary — no runtime required. Install via the curl / PowerShell one-liner above.
Unknown legacy keys in fln.json are rejected with Unknown config key. See CHANGELOG.md for the full 2.0 breaking list.
fln is free, open-source, and maintained by one developer.
If it saves you time or improves your AI workflow:
PRs and issues are welcome. Local gate: bun run verify (mirrors CI). See CONTRIBUTING.md for setup and AGENTS.md for architecture and invariants.
MIT © Eugene Nesvetaev
Local, explainable context compiler for AI coding agents. Analyze → plan → emit optimal context — with why/doctor diagnostics. No embeddings, no server.
Инструменты
Списка инструментов пока нет. У удалённых серверов он появляется после первой проверки состояния.
FAQ
Скопируйте на этой странице конфигурацию stdio для Cursor, Claude Desktop, Claude Code или VS Code. Она использует установку издателя, а не прокси PlugMCP.
В этой записи не указано обязательных переменных окружения.
Fln работает локально через stdio.
Последняя проверка: 2026-10-28. Local, explainable context compiler for AI coding agents. Analyze → plan → emit optimal context — with why/doctor diagnostics. No embeddings, no server.
