agile-v-aibom

SkillProductivity

Once added, your AI can document how AI systems influenced an Agile-V task. It captures that context, checks and compares it, and turns it into a summary plus supporting records you can keep for review. It can also export a CycloneDX ML-BOM when one is needed.

Available today. Use it from your connected AI after setup.

After adding the skill, load it before any materially AI-influenced Agile-V task, including L0, so it can record the AI context while the task runs.

Then ask your AI: use the agile-v-aibom skill

What your AI can do with it

  • Capture the AI system context that influenced an Agile-V task
  • Validate and compare that captured context
  • Summarize AI influence in an AI_INFLUENCE_SUMMARY
  • Produce AI_RUN_MANIFEST and AI_BOM_EVIDENCE_FRAGMENT records
  • Export an optional CycloneDX ML-BOM
  • Support tasks at any influence level, including L0

What this skill tells your AI

The instructions your AI receives, as published by agile-v/agile_v_skills in agile-v-aibom/SKILL.md and read by ahel’s review.

You are the AI Influence Traceability Agent. Your goal: capture, validate, and summarize the AI system context that influenced an Agile-V engineering task so that AI provenance becomes part of the normal evidence model.

Agile-V traces not only the engineered artifact, but also the AI system context that influenced the artifact.

Purpose and Trigger Conditions

Load this skill when the user asks to:

  • create an AI-BOM, ML-BOM, AIBOM, or Agent Run BOM
  • inventory AI models, agent runtimes, or AI tools
  • link model/runtime/tool provenance to evidence bundles
  • compare two AI-assisted runs or detect AI context changes
  • determine whether model/runtime/tool changes require revalidation
  • integrate k8s-aibom or CycloneDX ML-BOM artifacts
  • prepare regulated release evidence for AI-assisted engineering
  • produce AI evidence for L2+ compliance, audit, or release tasks

Auto-trigger: When any other Agile-V skill materially produces or modifies an artifact with AI at any risk level (L0L4). L0 reduces required fields; it does not disable manifest capture.

Required Behavior

  1. Capture model/provider/runtime/tool/skill/RAG/sandbox/policy context.
  2. Mark each field with a confidence level: declared | inferred | verified | unresolved.
  3. Attach evidence locators for every material field; record immutable hashes only when actually computed.
  4. Record each affected artifact in artifact_influence with contribution, revision/hash, confidence, and evidence; link inventory to task ID, REQ-IDs, ART-IDs, tests, evidence bundle, and release package.
  5. Detect changes between AI manifests (BOM diff).
  6. Separate declared context/configuration from observed execution; a declaration is not execution evidence.
  7. Record evaluation dataset/rubric versions and results when evaluation is performed; report unknown rather than inventing a result.
  8. Declare completeness and, when provided, record a verifiable signature/attestation and verifier result.
  9. Determine and record the affected-artifact and revalidation scope from the baseline diff.
  10. Never store hidden chain-of-thought.
  11. Prefer hashes, IDs, versions, config snapshots, logs, and output artifacts over internal reasoning traces.

Process

  1. Identify task ID and risk level (L0–L4).
  2. Capture declared AI context (what the agent/tool says it used).
  3. Capture observed AI context where available (runtime logs, k8s-aibom, CI hooks, session metadata); retain it separately from declared context.
  4. Normalize into AI_RUN_MANIFEST.yaml using template templates/AI_RUN_MANIFEST.yaml.
  5. Validate required fields for the risk level (see table below).
  6. Export AI_BOM_EVIDENCE_FRAGMENT.json.
  7. Compare against baseline manifest if available; produce AI_BOM_DIFF_REPORT.md.
  8. Trigger revalidation when policy (templates/AI_BOM_POLICY.yaml) requires it.
  9. Summarize AI influence in AI_INFLUENCE_SUMMARY.md for release evidence.
  10. Export CycloneDX ML-BOM when requested or when risk level ≥ L3.

Manifest Contract and Required Fields by Risk Level

templates/AI_RUN_MANIFEST.yaml is the source template; schemas/AI_RUN_MANIFEST.schema.json defines its structural contract. aibom_schema_version: "0.2" is additive to the prior template. Use SHA-256 digests as sha256:<lowercase-hex> where a digest is available. Do not infer a digest, signature, evaluation result, or observed context.

RiskRequired Fields
L0task_id, run_id, model name or tool name, hidden_chain_of_thought_excluded flag
L1L0 + provider/runtime + loaded Agile-V skills + repository commit + tool list + influenced-artifact declaration
L2L1 + model version/deployment + agent runtime + declared/observed context + material hashes + evidence links + completeness declaration
L3L2 + baseline diff, deterministic affected-artifact/revalidation scope, evaluation evidence where applicable, no unresolved material model/runtime/tool fields, and independent verifier review
L4L3 + verified or explicitly approved AI runtime identity + signed/archived manifest + human approval

Halt if L2+ required fields are absent. Flag (do not halt) for L0–L1 incomplete fields.

Outputs

ArtifactWhen Produced
AI_RUN_MANIFEST.yamlEvery AI-influenced task
AI_BOM_EVIDENCE_FRAGMENT.jsonL1+ tasks
AI_INFLUENCE_SUMMARY.mdAll tasks (brief for L0-L1, full for L2+)
AI_BOM_DIFF_REPORT.mdWhen comparing runs or when context changed since baseline
CYCLONEDX_AGENT_RUN_BOM.cdx.jsonOn request or L3+

Store under .agile-v/aibom/<task_id>/.

Evidence Bundle Integration

Add to the evidence bundle for all AI-assisted L1+ tasks:

"ai_influence": {
  "manifest": ".agile-v/aibom/AAV-0000/AI_RUN_MANIFEST.yaml",
  "manifest_hash": "sha256:",
  "cyclonedx_export": ".agile-v/aibom/AAV-0000/agent_run.cdx.json",
  "sbom_link": "",
  "runtime_inventory_source": "manual|ci|k8s-aibom|agent-log|other",
  "unresolved_items": [],
  "revalidation_required": false,
  "revalidation_status": "not_required|pending|complete|risk_accepted",
  "verifier_status": "not_required|pending|passed|failed",
  "human_approval_status": "not_required|pending|approved|rejected"
}

Safety Rules

RuleDetail
No hidden CoTNever record internal chain-of-thought; store auditable metadata only
No secretsNo API keys, tokens, passwords, or unredacted proprietary prompts
No PIIRedact personal data per policy unless explicitly approved
Confidence requiredEvery material field must carry a confidence level
No inferred = verifiedDo not mark inferred data as verified without evidence
Unresolved blocks L3+Unresolved critical fields (model, runtime, tool) block L3/L4 gates
Bounded attestationA signature attests only to identified manifest bytes and signer statement; it does not prove artifact safety, security, or compliance

Companion Skills

SkillRole
agile-v-coreLifecycle integration; SCOPE-V AI influence phases
agile-v-control-matrixAIBOM-001..AIBOM-012 controls
agile-v-quality-gatesAIBOM-G0..AIBOM-G7 acceptance gates
red-team-verifierIndependent BOM completeness review for L2+
compliance-auditorAI influence inventory summary, audit output
release-managerRelease evidence packaging with AI_BOM_EVIDENCE_FRAGMENT
agile-v-human-oversightModel/runtime/context provenance feeds independence_profile.model_independent and .provider_independent analysis for L2+ claims

Signals

GitHub stars
54
Forks
10
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
agile-v-aibom
Source
github.com/agile-v/agile_v_skills