RG_MCP_ALLOWED_ROOTS — Colon/semicolon-separated directories the server may read under. Defaults to the working directory. The server refuses any path outside these roots (blocks ../, absolute, and symlink escapes).
Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
The independent admission controller for AI systems.
Release-Gate combines code-level agent risk, external evaluations, runtime
traces, governance evidence, verification results and human approvals into an
auditable PROMOTE / HOLD / BLOCK decision, without requiring teams to
replace the tools that produced the evidence.
A PROMOTE means the candidate meets the declared release policy, with the
evidence and the gaps the decision lists. It is never a statement that a
release is safe.
Pre-deploy security auditor for AI agent code — the risks generic SAST misses.
API key
RG_MCP_ALLOWED_ROOTS
ตรวจสอบล่าสุด
2026-11-09
ดาว
—
เครื่องมือ
—
อัปไทม์
—
code-level agent risk SARIF from your scanner, or release-gate's own ──┐
external evaluations promptfoo, ProofAgent, red teams, eval harnesses ─┤
runtime traces OpenTelemetry, Langfuse, Arize-Phoenix ───────────┤ one candidate state,
verification results tests, provers, model checkers ───────────────────┼─▶ one claim graph, ─▶ PROMOTE / HOLD / BLOCK
governance evidence governance.yaml, the pinned AIBOM ────────────────┤ one declared policy + the Admission Report
human approvals reviews and approvals of this exact candidate ───┘
Where it sits
Each of these answers a different question. Release-gate reads the others'
results as attributed evidence and answers the last one.
Tool
The question it answers
Linter
Is the code well written?
SAST
Does the code contain known vulnerability patterns?
Guardrail
Should this live interaction be allowed?
Evaluator
How did the agent behave in these tests?
Observability
What happened when the system ran?
Release-Gate
Does the evidence establish that this exact candidate satisfies its release policy?
It does not re-run, re-grade or replace any of them. A promptfoo result stays
promptfoo's, a scanner's finding stays the scanner's, and the Admission Report
says which evidence release-gate produced itself and which it read from another
tool. Its own agent-code scanner is one producer among them, not the product.
What a decision says
Meaning
PROMOTE
the candidate meets the declared release policy with the evidence listed, and the gaps listed are ones the policy accepts
HOLD
something a person has to settle first, named, with the evidence that would settle it
BLOCK
the policy is violated: a failed check, a valid counterexample, a contradiction the policy blocks on
Unknown is never a pass. Every decision states what was not assessed, and
evidence about another state of the release does not count for this one. The
decision is deterministic from the declared policy and the evidence. Models can
be asked to read evidence, and their readings never decide.
How it works
flowchart LR
subgraph own["Release-gate's own checks"]
direction TB
o1["AST / taint scan"] ~~~ o2["PR diff"] ~~~ o3["governance"] ~~~ o4["trace validation"] ~~~ o5["loop sim, agent score"]
end
subgraph ext["Your tools"]
direction TB
e1["evals, red teams"] ~~~ e2["traces, SAST"] ~~~ e3["proofs, reviewers"]
end
sem["Semantic verifier<br/>bounded questions<br/>UNKNOWN on any failure"]
case["AssuranceCase<br/>claims, evidence, assumptions,<br/>contradictions, counterexamples,<br/>failed branches, coverage, independence"]
own --> case
ext --> case
sem -. "a reading, never a verdict" .-> case
case --> policy{"declared<br/>policy"} --> out["PROMOTE / HOLD / BLOCK"]
The invariant. Release-Gate may generate evidence, ingest evidence, normalize evidence, compare evidence, semantically interpret bounded evidence, and determine whether evidence satisfies policy. It must never pretend that one model, one scanner, one evaluator, one score, or one successful test establishes universal truth.
Each claim ends in one status, and the declared policy says which statuses admit:
flowchart LR
ev["the evidence<br/>on one claim"] --> claim{"a claim"}
claim -- "a valid counterexample<br/>(outranks any support)" --> c["CONTRADICTED"]
claim -- "a bound proof, or two<br/>independent groups of checks" --> e["ESTABLISHED"]
claim -- "support short of that" --> s["SUPPORTED or<br/>PARTIALLY_SUPPORTED"]
claim -- "only support about<br/>another state" --> u["UNSUPPORTED"]
claim -- "inconclusive or unreadable" --> k["UNKNOWN"]
claim -- "nothing bears on it" --> n["NOT_ASSESSED"]
No score is an input, and copies of one test from one session count once.
ARCHITECTURE maps each box to
its code. tests/test_product_invariant.py executes every clause of the
invariant.
Try it
pip install release-gate
release-gate assure your-run.jsonl # no config file, no YAML, no account
That works on an OpenTelemetry trace, a Langfuse export, a promptfoo result, or
release-gate's own record format: the shape is detected, not declared. You get a
verdict, what a person has to look at, and what would resolve it.
In a pipeline, the release's claims and everything the pipeline produced decide
together:
Exit 0 PROMOTE, 10 HOLD, 1 BLOCK. CI templates cover
GitHub Actions, GitLab, Jenkins, CircleCI and Azure Pipelines.
Release-gate's own checks are evidence too. The --json of pr, verify,
loop-sim and agent-score is read like any tool's. Here is a release that
promotes on its own, plus one trace that called a tool its governance file
forbids:
# examples/evidence/first-party/verify.json was written by
# release-gate verify governance.yaml --trace trace.json --iteration 2 --cost 0.06 --json
release-gate assure examples/agents/02-release-promoted.jsonl \
--evidence examples/evidence/first-party/verify.json \
--methodology [email protected] --admission
Decision BLOCK
BLOCK under [email protected] and rg-resolution@1: 2 blocking condition(s) established — RG-CONTRA-002 (contradictions, on rg-trace:run-2291); RG-VERIF-002 (claim_status, on rg-trace:run-2291)
The block comes from the failed trace check, not from the verifier's own
ROLLBACK. That verdict is recorded and decides nothing.
Or run the worked examples. In six tools, one release, one decision,
five tools report good news and the decision still holds, for the reason it
prints. Five agent runs cover an OpenTelemetry trace, a promptfoo eval, a
destructive migration, a research swarm, and one that promotes:
python examples/demo-admission/run_demo.py
cd examples/agents && ./run-all.sh
The product's acceptance test is one more. One enterprise release, end to end
admits AI-generated code whose tools move money, over every kind of evidence.
It answers each question a release owner asks, and shows that no score, model
judgment or test count outvotes the counterexample it contains:
python examples/acceptance/run_acceptance.py
Three things a scanner or a score cannot do
1. It reduces machine work to a list a person can actually read
Two million records is not reviewable. A score over two million records is not
reviewable either — it is one number standing in for a judgement nobody made.
Release-gate returns a bounded set of things that need a human, derived from
which claims the decision actually rests on:
distinct producers
records seen
evidence
claims
reaches a person
one agent, one action
4
7
6
0
1 item
10,248 workers
10,254
2,287,133
10,258
2,420
13 items, 7 undroppable
Every figure in that table is measured by the test suite, not written here by
hand — a claim that drifts from the implementation fails a test.
Criticality comes from reachability in the claim graph, never from volume — a
claim one agent emitted once is exactly as load-bearing as one four hundred agents
discussed.
And a shorter list is not a better case. That is a property in code that
cannot return anything else, because the one dangerous way to read this table is
that a smaller number is a win. It can equally mean detection got worse.
2. Every verdict says what it did not check
This is the part most tools skip. A pass that doesn't state its own coverage is
indistinguishable from a pass that never looked.
WHAT WAS ASSESSED
[ assessed] input_integrity: the input file was hashed by release-gate
[ assessed] record_mapping: 6 of 6 record(s) mapped; 0 skipped
[NOT_ASSESSED] execution_reconstruction: no execution graph was reconstructed
[NOT_ASSESSED] replication: no verification attempt names a target
[NOT_ASSESSED] adversarial_review: no verifier set out to disprove this
NOT_ASSESSED is a first-class answer, kept apart from "we looked and found
nothing" everywhere in the engine. So is UNKNOWN, and so is a refuted check as
against an unresolved one. Collapsing those is how a gap comes to read as a clean
bill of health.
3. When it holds, it returns the work order
A gate that only says no is a nag. Each item comes with what would close it:
[BLOCK] RG-ACT-001 'execution_reconstruction' is stated as NOT_ASSESSED
→ supply the run's trace or tool-call log
[ADVISORY] RG-PROV-002 all evidence traces to a single producer
→ add evidence from an independently-operated producer
That list is machine-readable (--json), so the next agent run can go and get the
evidence rather than a human re-reading the case to work out what was missing.
What it will not tell you
Not that a release is safe. Not that a result is guaranteed correct. Not
that the gate is unhackable — twenty attacks run against the engine itself and
one is recorded NOT_DEFENDED with what bounds it instead. Not that a case is
uncontested, that hallucinations are solved, or that an expert has been
replaced: the output is a list of what needs a person.
Each refusal is a property in code that cannot return anything else.
docs/POSITIONING.md names every one with the line that
enforces it.
From Python
import release_gate as rg
case = rg.create_case(objective="Deploy generated migration", subject=migration)
case.add_execution(trace) # the steps, or a native trace
case.add_verification(test_result, method="TEST_SUITE", outcome="PASSED",
verifier="ci://pytest", against_subject=True)
decision = case.finalize() # PROMOTE / HOLD / BLOCK, with its coverage attached
print(decision.required_evidence)
The same four calls carry one agent's migration and a ten-thousand-worker research
run. Not two products with a shared name — one code path: 346 engine functions
are common to both, 87% of everything the single-agent path touches.
Configuration
Nothing is required to run. A methodology is what turns structure into a
verdict — without one, release-gate reports everything structural it can see and
holds, because "is this enough?" is a domain question and inventing an answer
would be claiming a standard it does not have.
Organisation config (--config) layers your own standards on top and can only
ever tighten. The methodology, the resolution policy (--resolution-policy:
what it takes to establish a claim, what a counterexample does) and the
organisation config together are the declared release policy a PROMOTE is
measured against. Each is digested into the case.
Evaluations, red teams, SAST, formal verification, reviews, behavioural evaluations and containment drills, each through one documented contract. Read and attributed, never re-run
Release-gate's own evidence producer for code-level agent risk: AST and taint analysis of model output reaching eval/pickle, retrieved text reaching prompts, uncapped LLM loops. Measured on its own 93-case corpus
PR diff analysis (pr), trace validation (verify --trace), loop simulation (loop-sim) and the agent score (agent-score). Their --json is evidence assure --evidence reads like any producer's; their own verdicts and scores are recorded and decide nothing
Optional. A model, or a panel of independent models, reads evidence the rules cannot. Its readings are recorded and never decide; disagreement goes to a person
Producers sign their output (release-gate sign, DSSE / in-toto). assure --trusted-keys checks each signature against keys trusted for named producers, and does not read evidence whose signature fails
A production failure becomes a counterexample that every later release must answer. A recorded kill-switch drill (containment/1) is the evidence behind "it can be paused"
--resolution-policy diversity-strict@1: critical claims need two independent groups of checks, where a shared provider counts as one group, plus a check by someone other than the author
evidence-pack writes JSON, Markdown and HTML. The sealed case (--case-output) is content-addressed and verifiable. None of these is signed unless you sign it
The scanner, the assurance layer and semantic providers, measured separately. The assurance corpus publishes no headline precision figure, because on most of its cases precision is not a meaningful thing to measure