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SDLC Evidence Packet

sdlc_evidence_packet
Read-onlyIdempotent

Collect versioned evidence for a GitHub issue, pull request, or release, recording unverified caller assertions in a read-only packet.

Instructions

Generate a versioned, read-only evidence packet for one Issue, pull request, or release ref.

Repository text is treated as untrusted data. Caller assertions remain unverified. Markdown is rendered from the structured packet and high-confidence prompt injection is omitted from the Markdown channel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoGitHub repo. Falls back to GITHUB_REPO.
ownerNoGitHub owner. Falls back to GITHUB_OWNER.
subjectYesExactly one Issue, pull request, or release ref to collect.
callerAssertionsNoOptional caller-authored statements. Always recorded as unverified.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
budgetYes
subjectYes
summaryYes
evidenceYes
collectedAtYes
limitationsYes
contentDigestYes
schemaVersionYes
trustBoundaryNo
omittedEvidenceYes
generatorVersionYes
recommendedNextActionsYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, open world, idempotent. Description adds valuable context: repository text is untrusted, caller assertions unverified, and high-confidence prompt injection is omitted from Markdown. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with purpose, each sentence adds specific value. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given annotations and output schema exist, the description sufficiently covers the tool's behavior. Could elaborate on versioning or packet contents, but the output schema likely covers that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good descriptions. The description restates the subject scope but does not add new parameter-level meaning beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it generates a versioned, read-only evidence packet for one Issue, pull request, or release ref. Distinguishes from sibling tools like plan_from_context or quality_gate_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives. Only describes what it does, but fails to mention context or exclusions despite having many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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