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finalize_handoff

Produce a canonical Markdown handoff for completed documentation audits, validating evidence references against session retrievals and persisting an immutable, session-scoped receipt.

Instructions

Finalize one canonical Markdown handoff for a completed documentation audit/analysis (jdocmunch.handoff/v1; suite parity with jCodeMunch). The server assembles YOUR sections deterministically, validates every evidence_refs entry against what this session actually retrieved (section ids or doc paths served by search_sections / search_titles / get_section / get_sections — unknown refs fail closed), persists the result session-scoped, and returns a compact receipt {handoff_id, resource_uri, sha256, length, canonical:true}. Read the immutable body via the munch://handoff/ resource; repeated reads are byte-identical. Appendices are included exactly once; no character limit; never writes to the documentation corpus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesDoc repo identifier the handoff is about.
taskYesThe task/question this handoff answers (becomes the title).
profileNoHandoff profile label (e.g. doc_audit).general
sectionsYesOrdered report sections, each {heading, content} (markdown). The caller authors these; the server only assembles. Optional per-section claims[] bind evidence to an individual claim instead of one global list (handoff/v2).
appendicesNoOptional named appendices, each {name, content, content_type?}; names must be unique.
evidence_refsYesSection ids or doc paths retrieved this session; validated against the session retrieval record.
Behavior5/5

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

Annotations declare readOnlyHint=false, and the description adds rich behavioral details: deterministic assembly, validation of evidence_refs against session-retrieved data (fails closed), session-scoped persistence, return of receipt, immutable resource, appendices once, no character limit, no corpus writes. No contradiction.

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

Conciseness4/5

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

Description is detailed but each sentence adds necessary information. Well-structured with purpose first, then behavior details. Slightly long but not verbose.

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 complexity and lack of output schema, description fully explains inputs, behavior, validation, failure mode, persistence, and output format. Complete for an AI agent to use correctly.

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

Parameters4/5

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

Schema coverage is 100% with good descriptions. Description adds value by explaining caller authors sections, server only assembles, and evidence_refs validation. Adds context beyond schema.

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 the tool finalizes a Markdown handoff for a completed documentation audit/analysis, with specific verb and resource. Distinguishes from sibling tools which are all read-oriented or different operations (search, index, etc.).

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

Usage Guidelines4/5

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

Explicitly says 'for a completed documentation audit/analysis', providing context. Does not explicitly contrast with alternatives, but the sibling tools are clearly different (read/search tools), making usage clear.

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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