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delimit_evidence_collect

Collect evidence artifacts from deployments, audits, or tests to create verifiable bundles for governance attestation.

Instructions

Collect evidence artifacts for governance (Pro).

When to use: after a deploy, security audit, test run, or other gate event — to capture an evidence bundle that delimit_evidence_verify can later attest. When NOT to use: to verify an existing bundle (use delimit_evidence_verify) or query the contract ledger (delimit_ledger).

Sibling contrast: delimit_evidence_verify verifies; delimit_ledger queries the chain; this collects new evidence.

Side effects: gated by require_premium. Writes a new evidence bundle via backends.repo_bridge.evidence_collect.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNoRepository or task path. Default "." (cwd)..
evidence_typeNoType of evidence — e.g. "deploy", "security", "test", "audit". Stored in bundle metadata. Empty = generic.
asset_metaNoOptional JSON string with asset provenance metadata (for evidence_type='asset').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Even without annotations, the description fully discloses behavioral traits: it writes a new evidence bundle, is gated by require_premium (implying a paywall/mutation), and explains the backend. 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?

Concise, well-structured with sections for purpose, usage, contrast, and side effects. Every sentence adds value with no redundancy.

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

Completeness5/5

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

Given the tool's simplicity (3 optional params, output schema present), the description covers workflow context, usage guards, and side effects. It is complete for an AI agent to select and invoke correctly.

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%, so the description does not need to add much. It does not elaborate beyond schema, but the baseline of 3 is appropriate as the schema already documents parameters well.

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?

The description uses a specific verb 'collect' and resource 'evidence artifacts for governance'. It clearly distinguishes from sibling tools delimit_evidence_verify and delimit_ledger by their functions.

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

Usage Guidelines5/5

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

Provides explicit 'When to use' scenarios (deploy, security audit, test run, gate events) and 'When NOT to use' with alternative tool names, plus a sibling contrast section. This is exemplary usage guidance.

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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