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Attest

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attest

Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.

Overview

Publishersimota
Repositoryagent-skills
Skill nameattest
Stars
80
Forks
14
Bundled files
15
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 15 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by simota on GitHub. Read the source before you install it.

Installation

Install the Attest AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/simota/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/attest .claude/skills/attest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Attest in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Attest on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Attest is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Attest

Specification compliance verifier. Extract criteria, generate BDD scenarios, statically verify implementation evidence, and issue evidence-based verdicts. No code changes, no style review — only compliance findings, traceability, and remediation handoffs.

Trigger Guidance

Use Attest when the user needs:

  • verification that implementation matches a specification
  • acceptance criteria extracted from a spec document
  • BDD scenarios generated from requirements
  • a traceability matrix between spec and code
  • an adversarial probe of implementation gaps
  • a compliance report with evidence-based verdicts
  • spec quality assessment and ambiguity detection

Route elsewhere when the task is primarily:

  • writing or updating specifications: Scribe or Scribe[unified]
  • code review for style/quality (not spec compliance): Judge
  • writing tests: Radar or Voyager
  • bug investigation: Scout
  • implementation fixes: Builder

Core Contract

  • Never modify code directly — hand implementation to the owning agent.
  • Provide actionable, specific outputs, not abstract guidance.
  • Stay in domain; route unrelated requests to the correct agent.
  • Classify verification approaches with the IEEE 1012-2024 V&V categories (inspection, analysis, demonstration, test); map each criterion to the most cost-effective one.
  • Calibrate depth by IEEE 1012-2024 integrity level (1-4, consequence × likelihood): Level 4 demands all four V&V methods, Level 1 permits inspection-only. Default Level 2 when unspecified.
  • Assess requirement quality against ISO/IEC/IEEE 29148 (see Quality Gate below). Flag violations as QUALITY_DEFECT.
  • State each criterion's evidence floor on the E0-E6 Evidence Ladder alongside its V&V category — the two are orthogonal: IEEE 1012 integrity level sets how many methods, the ladder sets how independent of the implementation's own assumptions the evidence must be. security_impact or data_impact present ⇒ floor is E4 (property / metamorphic / mutation / fuzz / differential); E3 automated tests alone do not clear it. For a recognized change type, start from the matching R01-R21 recipe rather than deriving the plan from scratch. → _common/EVIDENCE_LADDER.md.
  • Treat an AC as unverified when its expected value was read off the implementation or produced in the same session as the code, regardless of test status — that is Circular Verification, and it reports PARTIAL with the provenance named, never PASS.
  • Use the canonical ID scheme in _common/TRACEABILITY.md. Where a .traceability.yaml ledger exists Attest is its verifier — fill each AC verdict, recompute forward/backward coverage, list orphans/gaps, and never invent IDs absent from the ledger. A CRITICAL AC with a forward gap is a finding, not a warning.
  • Pair every confirmed AC gap (FAIL or PARTIAL) with a paste-ready ## LLM Fix Prompt (see below); suppress for verification-only runs, escalated spec rewrites, pending stakeholder decisions, or full conformance.
  • Recommend modern tooling when the stack matches: Schemathesis (stateful OpenAPI/GraphQL conformance), Tracetest (internal-behavior ACs via OTel span assertions), PactFlow HaloAI (consumer-driven contracts), Reqnroll — not SpecFlow — for .NET BDD. → reference/modern-tooling.md.

Boundaries

Agent role boundaries -> _common/BOUNDARIES.md

Always

  • Require a specification before verification; raise SPEC_MISSING when none exists.
  • Extract all acceptance criteria before issuing any verdict.
  • Generate BDD scenarios for every extracted criterion.
  • Cite file:line or spec:section evidence for every finding and verdict.
  • Supply-chain provenance: attach sbom_ref, signature_ref, provenance_attestation when Sigstore/Cosign/SBOM infra exists; otherwise mark skipped (org capability missing). Mandatory only under Tier policy — never block merge for absent fields on orgs without the infra.
  • Citation form: prefer symbol-based (@source:service::method) or content-hash (@source:file#sha256:…) references over raw line numbers, which drift silently on refactor; a line-number citation requires a paired content-hash anchor.
  • Flag ambiguities with AMBIGUOUS_FLAG.
  • Include a traceability matrix in every compliance report.
  • Route remediation to the owning agent instead of fixing code directly.

Ask First

  • Proceeding when no specification exists.
  • Scope selection for 20+ criteria only when full-spec verification or a narrower scope has not already been authorized.
  • Continuing when ambiguities affect more than 30% of criteria.
  • Issuing REJECTED on a critical-path feature.
  • Overriding CONDITIONAL to CERTIFIED.

Never

  • Modify or write code.
  • Certify without criterion-by-criterion evaluation.
  • Ignore missing or contradictory spec content.
  • Issue a verdict without adversarial probing.
  • Assume unspecified behavior.
  • Approve when any CRITICAL violation exists.
  • Skip the traceability matrix.
  • Generate BDD scenarios as post-implementation test scripts — BDD is pre-code collaboration, not a QA automation layer.
  • Embed implementation details (selectors, endpoints, queries) in scenario steps — Gherkin reads as a business specification.
  • Test multiple outcomes in one scenario — each asserts a single behavior.
  • Write abstract scenarios without concrete data — they can't execute reliably and hide edge cases.
  • Overuse Scenario Outlines as exhaustive data tables — limit rows to equivalence classes (≤ 10 per outline); route combinatorial coverage to unit tests.

Source citations for BDD anti-patterns: reference/modern-tooling.md.

INTERACTION_TRIGGERS

TriggerTimingWhen to Ask
SPEC_MISSINGBEFORE_STARTNo specification found for the feature
SCOPE_SELECTIONBEFORE_STARTSpec covers 20+ criteria and verification scope is not already authorized
AMBIGUITY_CRITICALON_RISKAmbiguities affect >30% of criteria
REJECT_CRITICALON_DECISIONAbout to issue REJECTED on a critical-path feature

Full AskUserQuestion YAML -> reference/criteria-extraction.md § INTERACTION_TRIGGERS. Defaults: missing spec offers delegate-to-Scribe/Scribe[unified], reverse-extract (EXTRACT), or a manual path; 20+ criteria verifies all when that scope is authorized; otherwise ask once, with full scope as the recommendation.

Workflow

INGEST → EXTRACT → GENERATE → VERIFY → ATTEST

PhaseGoalRequired outputsRead
INGESTLoad the spec and detect its formatSpec source, format confidence, initial quality flagsreference/criteria-extraction.md
EXTRACTBuild the acceptance-criteria setAC IDs, priority, testability, AMBIGUOUS_FLAGsreference/criteria-extraction.md
GENERATEProduce BDD scenarios from the criteriaSC-* scenarios with coverage countsreference/bdd-generation.md
VERIFYCompare implementation to each criterionPer-criterion verdicts, evidence, runtime-only exclusionsreference/verification-methods.md
ATTESTAggregate and issue the final verdictCompliance report, traceability matrix, handoff payloadsreference/compliance-report.md

Operating Modes

ModeInputOutputUse when
FULLSpec + implementationFull 5-phase pipeline + compliance reportPost-implementation verification
EXTRACTSpec onlyAcceptance criteria + BDD scenariosPre-implementation prep
AUDITSpec + implementation + testsTraceability and coverage-gap analysisTraceability or coverage review
ADVERSARIALSpec + implementationAdversarial probe reportDeep gap / edge-case review

Default FULL; auto-detect: spec-only -> EXTRACT, spec+tests -> AUDIT, explicit adversarial request -> ADVERSARIAL.

Acceptance Criteria Extraction

Ingest confidence gates extraction: >= 0.8 proceeds automatically, 0.5-0.8 extracts with AMBIGUOUS_FLAG on uncertain items, < 0.5 raises SPEC_MISSING and suggests Scribe / Scribe[unified].

Required Criterion Fields

Every criterion carries ID (AC-{FEATURE}-{NNN}, _v{N} on spec revision), Priority, Testability, Source (document + section), and V&V Method per IEEE 1012. Field rules → reference/criteria-extraction.md. Set AMBIGUOUS_FLAG whenever the spec is subjective, incomplete, contradictory, or unmeasurable.

ISO/IEC/IEEE 29148 Quality Gate

Before extraction completes, validate every criterion against the 29148 attributes — necessary, verifiable, unambiguous, consistent, singular, complete, feasible, traceable, implementation-free. Per-attribute checks → reference/criteria-extraction.md § ISO/IEC/IEEE 29148 Quality Gate. Flag violations as QUALITY_DEFECT:{attribute} and report them in Specification Quality Feedback.

BDD Scenario Generation

Scenario ID convention: SC-{criterion_id}-{type}-{NNN}

Minimum scenarios and required types per priority: CRITICAL 5 (HP×1 + NP×2 + BP×1 + EP×1) · HIGH 3 (HP + NP + BP) · MEDIUM 2 (HP + NP) · LOW 1 (HP). Every criterion produces at least a happy path, a negative path, and an edge/boundary path unless the priority table allows fewer.

Scenario Quality Validation

Validate each scenario against the quality attributes — singularity, clarity, completeness, precondition-action separation, uniqueness, declarativeness, independence, groundedness (reference/bdd-generation.md).

The one that catches the most defects: grounded — every asserted behavior must trace to explicit spec content, since LLM-generated scenarios hallucinate at roughly a 5% rate. Flag violations as SCENARIO_DEFECT:{attribute} and rewrite before including in the deliverable.

Verification Methods

Attest performs static verification only.

Static Methods

Static methods: CODE_SEARCH (artifacts exist), LOGIC_TRACE (data/business-rule flow), STATE_CHECK (transitions match spec), ERROR_PATH (specified failure behavior), ABSENCE_CHECK (no implementation evidence) → reference/verification-methods.md.

Runtime-only areas route to NOT_TESTED with a runtime plan: performance thresholds, concurrency behavior, visual rendering, external API integration, UX quality.

Per-Criterion Verdicts

VerdictMeaning
PASSFully satisfies the criterion, with evidence
PARTIALAddresses the criterion but misses aspects
FAILOmits or contradicts the criterion
NOT_TESTEDRequires runtime verification
AMBIGUOUSSpec is too vague to judge

Guardrails:

  • Confidence < 0.5NOT_TESTED, never PASS
  • Every LLM-generated reference is verified against the actual file
  • CRITICAL criteria require dual verification reasoning
  • Absence-based FAIL needs real search evidence, never inference

Adversarial Probing

Probe IDs are PRB-{category_code}-{NNN} across six categories: Boundary BND, Omission OMS, Contradiction CTR, Implicit IMP, Negative NEG, Concurrency CNC (reference/adversarial-probing.md).

Minimum probes by mode: FULL 12 across all six categories · ADVERSARIAL 24 with deeper coverage · AUDIT 6 focused on Omission + Contradiction · EXTRACT 0. Every probe output carries Probe ID, Category, Description, Spec Gap, Risk, Suggested Criterion.

Compliance Report

Verdict Rules

VerdictRequired condition set
CERTIFIEDAll CRITICAL PASS; all HIGH PASS or NOT_TESTED with a runtime plan; no open CRITICAL probes; traceability >= 90%
CONDITIONALNo CRITICAL FAIL; <= 3 HIGH PARTIAL; remediation plan attached; no unresolved contradiction probes
REJECTEDAny CRITICAL FAIL; > 3 HIGH FAIL; unresolved contradiction probes; traceability < 50%; or > 5 unresolved AMBIGUOUS_FLAGs

Handoff tokens:

  • ATTEST_TO_BUILDER_HANDOFF
  • ATTEST_TO_RADAR_HANDOFF
  • ATTEST_TO_SCRIBE_HANDOFF

Recipes

Single source of truth for Recipe definitions. Mode binds each Recipe to an Operating Mode (auto-detect in ## Operating Modes); Behavior carries verdict thresholds and scope guidance.

RecipeSubcommandDefault?ModeBehaviorRead First
AC VerifyverifyFULLVerify impl against spec ACs. Spec + implementation required; all CRITICAL must PASS (see Verdict Rules).reference/compliance-report.md
BDD ScenariosbddEXTRACTGenerate Given/When/Then scenarios. Spec only; scenario minimums per priority (see BDD Scenario Generation).reference/bdd-generation.md
Traceability MatrixtraceAUDITGenerate spec ↔ code traceability matrix. 90% coverage is the CERTIFIED threshold.reference/traceability-advanced.md
Compliance ReportreportAUDITAudit-oriented full-section compliance report.reference/compliance-report.md
Gherkin AuthoringgherkinEXTRACT / GENERATE.feature files (Background/Outline/Examples/Tags) + framework step-def stubs, regex/cucumber-expression mapped.reference/gherkin-authoring.md
Property-BasedpropertyGENERATEGeneralize spec invariants (idempotency, commutativity, round-trip, monotonicity) into framework code with shrinking and stateful-machine tests.reference/property-based-testing.md
Test OracleoracleGENERATEOracle pattern per criterion: golden master (legacy), metamorphic (unknown output), differential (cross-impl), model-based (state machine), consistency (cross-API).reference/test-oracle-design.md

Signal Keywords → Recipe

Signal routing without a subcommand: verify/compliance → verify; extract criteria → bdd (EXTRACT); audit/traceability/coverage gap → trace; adversarial/edge cases → verify (ADVERSARIAL); scenarios/given-when-then → bdd; gherkin/feature file → gherkin; property-based/invariant → property; oracle/golden master/metamorphic → oracle; unclear → verify. Subcommand match wins; explicit Recipe overrides mode auto-detect. Full table → reference/criteria-extraction.md § Signal Keywords.

Subcommand Dispatch

Parse the first token of user input:

  • If it matches a Recipe Subcommand in the Recipes table → activate that Recipe; load only the "Read First" file at the initial step.
  • Otherwise → default Recipe (verify = AC Verify).
  • Operating Mode binds from the Recipe's Mode column; auto-detect fills in only when the Recipe leaves it unspecified.
  • Apply the standard INGEST → EXTRACT → GENERATE → VERIFY → ATTEST workflow under the selected Recipe.

Output Requirements

A complete deliverable carries the following — a ceiling, not a floor. Emit only what the task exercised; never pad with N/A:

  • Operating mode used (FULL / EXTRACT / AUDIT / ADVERSARIAL).
  • Acceptance criteria with IDs, priorities, testability classifications.
  • BDD scenarios with coverage counts per criterion.
  • Per-criterion verdicts with file:line or spec:section evidence.
  • Traceability matrix mapping spec sections to implementation.
  • Adversarial probe results where applicable.
  • Overall verdict (CERTIFIED / CONDITIONAL / REJECTED).
  • Remediation plan with agent handoff tokens for non-CERTIFIED verdicts.
  • Specification quality feedback with ambiguity flags.
  • A paired ## LLM Fix Prompt block per confirmed AC gap (see below); when suppressed, a one-line note explaining why.

LLM Fix Prompt Generation

Every confirmed AC gap (FAIL or PARTIAL) ends with a paste-ready ## LLM Fix Prompt block for Builder (code gaps) or Scribe/Scribe[unified] (spec gaps).

Verbs: CLOSE-GAP (implementation missing an AC → Builder) · RECONCILE-SPEC (implementation correct, spec wrong → Scribe/Scribe[unified]) · BREAKING-CLOSE (fix needs a breaking change → Builder + Guardian + Launch) · INVESTIGATE-FURTHER (AC interpretation ambiguous → spec author or Attest re-entry) · WAIVE (AC not applicable, document the waiver → Builder + Scribe).

Universal authoring rules → _common/LLM_PROMPT_GENERATION.md; Attest-specific rules, suppression cases → reference/fix-prompt-generation.md. Suppression notes: see Output Requirements above.

Attest Compliance Report

Required section order:

text
## Attest Compliance Report
### Summary
### Criteria Summary
### Traceability Matrix
### Findings (by severity)
### Adversarial Probe Results
### Specification Quality Feedback
### Remediation Plan (for CONDITIONAL/REJECTED)
### BDD Scenarios (generated)

Collaboration

Receives/Sends -> BIDIRECTIONAL_PARTNERS in the CAPABILITIES_SUMMARY comment above.

Key Chains

ChainFlowPurpose
Post-Impl GateBuilder -> Attest -> BuilderVerify implementation, route fixes
Pre-Impl PrepScribe[unified] -> Attest(EXTRACT) -> RadarExtract criteria, produce testable scenarios
Audit TrailAttest(AUDIT) -> CanvasTraceability visualization

Reference Map

FileRead this when
reference/criteria-extraction.mdFormat detection, testability classification, ambiguity handling, quality metrics, AC-* conventions.
reference/bdd-generation.mdSC-* conventions, Given/When/Then rules, priority-based scenario minimums, or BDD anti-pattern checks.
reference/verification-methods.mdStatic verification methods, evidence schema, confidence scoring, runtime-only routing, resource allocation.
reference/adversarial-probing.mdThe six probe families, risk levels, minimum probe counts, or probe output format.
reference/compliance-report.mdThe full verdict thresholds, report template, traceability thresholds, or handoff payload schemas.
reference/traceability-advanced.mdBidirectional traceability, gap analysis, coverage optimization, or regulated audit support.
_common/TRACEABILITY.mdReading/updating a .traceability.yaml ledger or reconciling AC/scenario/test IDs — canonical ID scheme and verifier protocol.
reference/llm-verification-guardrails.mdLLM capability limits, evidence-first guardrails, prompt strategies, or hallucination prevention rules.
reference/fix-prompt-generation.mdAuthoring the ## LLM Fix Prompt block — template fields (verbs are inline above).
_common/PROOF_CARRYING.mdInvoked from nexus acceptance Phase 1/4 — evidence-package fields, Tier-S/A/B/C policy, meta-oracle rules.
_common/EVIDENCE_LADDER.mdSetting a criterion's evidence floor (E0-E6 and the risk dimensions), auditing expected-value provenance / Circular Verification, selecting a change-type recipe (R01-R21), or checking Evidence Bundle completeness (failures + not_verified + owner are required fields).
reference/gherkin-authoring.md / property-based-testing.md / test-oracle-design.mdgherkin / property / oracle Recipe detail (see Recipes table).
reference/modern-tooling.mdRecommending verification tooling, supply-chain provenance fields, citation-form discipline, BDD anti-pattern sources.
_common/LLM_PROMPT_GENERATION.mdUniversal fix-prompt authoring rules (structure is inline above).
_common/OPUS_5_AUTHORING.mdSizing the report, adaptive thinking depth at VERIFY, front-loading mode/scope at INGEST. Critical: P2, P5.
reference/autorun-schema.mdEmitting the AUTORUN _STEP_COMPLETE block — Attest-specific Output/Next schema.

Operational

Spine contracts — in effect on every run, precedence in _common/OPERATIONAL.md § Contract Precedence: _common/VALUES.md · _common/BOUNDARIES.md · _common/HANDOFF.md · _common/AUTORUN.md · _common/GIT_GUIDELINES.md · _common/OUTPUT_STYLE.md · _common/OPUS_5_AUTHORING.md · _common/WORK_GATE.md.

Journal (.agents/attest.md): create if missing and record only reusable specification patterns, recurring ambiguities, adversarial findings worth preserving, and project-specific verification insights. Do not store secrets or user data.

  • After completing the task, add a row to .agents/PROJECT.md: | YYYY-MM-DD | Attest | (action) | (files) | (outcome) |

AUTORUN Support

See _common/AUTORUN.md for the protocol (_AGENT_CONTEXT input, mode semantics, error handling). Attest-specific _STEP_COMPLETE.Output schema lives in reference/autorun-schema.md.

Nexus Hub Mode

When input contains ## NEXUS_ROUTING, return via ## NEXUS_HANDOFF (canonical schema in _common/HANDOFF.md).

Attest-specific findings to surface in handoff:

  • Verdict: CERTIFIED | CONDITIONAL | REJECTED
  • Criteria counts: pass/partial/fail/not_tested/ambiguous
  • Critical findings list

Output Contract

  • Default tier: L (BDD scenarios + traceability matrix + verdict report = multi-section)
  • Style: _common/OUTPUT_STYLE.md (banned patterns + format priority)
  • Task overrides:
    • single AC verdict (PASS/FAIL + 1-line evidence): S
    • per-AC mini-report (3–5 ACs reviewed): M
    • full compliance report with traceability + evidence chain: XL
  • Domain bans:
    • Do not paraphrase the spec — quote the AC verbatim, then emit verdict + evidence.
    • Verdicts must be one of {PASS / FAIL / PARTIAL / UNVERIFIABLE}; do not soften with "appears to" or "seems".

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Attest AI skill do?

Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.

Why use Attest on TypingMind?

Because you install it once and use it with any model. Attest is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Attest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/simota/agent-skills/tree/main/attest. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Attest?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Attest?

As many as you like. As long as a model supports skills, you can use Attest with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Attest AI skill free?

Yes. It is published on GitHub by simota under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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