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Faneraiy14
by Faneraiy14

Записати архітектурну документацію репо з прив'язкою до коміту

write_doc

Save documentation to a repo's Architecture file and record the current commit hash, enabling stale-doc detection by counting commits since the write.

Instructions

Записує ~/Projects/Architecture/.txt і поруч фіксує commit-хеш репозиторія на момент запису. Після цього check_docs може рахувати РЕАЛЬНУ кількість комітів з моменту запису (git rev-list --count) замість грубого порівняння за mtime файлу. Текст документації інструмент не генерує - лише зберігає вже готовий текст (розуміння коду для документування лишається завданням AI/людини).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesНазва теки репозиторія (напр. "anylint")
contentYesПовний текст документації для запису в <repo>.txt
docsRootNoТека з .txt-документацією (типово "<projectsRoot>/Architecture")
projectsRootYesАбсолютний шлях до теки з репозиторіями (напр. "/home/sviat/Projects")
Behavior4/5

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

No annotations are provided, so the description carries the transparency burden. It discloses the file write, the commit-hash capture, the downstream benefit for check_docs, and the limitation that documentation text is not generated. It does not detail overwrite behavior or failure conditions, but these are minor for this kind of persistence tool.

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?

The description is three focused sentences: what it writes, why the commit-hash matters, and what it does not do. The operational facts are front-loaded and every sentence carries distinct information without redundancy.

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?

For a write tool with a fully documented schema, the description gives enough context for correct invocation: output path pattern, content expectation, commit-hash recording, and the relationship to check_docs. It does not specify return values or explicit prerequisites, but no output schema exists and the provided context is otherwise adequate.

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 description coverage is 100%, so all four parameters are already documented and the baseline is 3. The description adds a little contextual meaning, such as repo being used in the output filename and content being pre-existing text, but it does not materially change the parameter semantics beyond the 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?

The description names a concrete action — writes documentation to ~/Projects/Architecture/<repo>.txt — and uniquely adds the commit-hash side effect. It also clearly states what the tool does not do (does not generate documentation text), which distinguishes it from siblings like check_docs and check_release_drift.

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?

The description makes the intended sequence clear: write with this tool first, then check_docs can use the recorded commit hash for accurate counting. It also explicitly says the tool only saves already-prepared text, so an agent knows not to invoke it for generation. It stops short of naming explicit alternatives or when-not-to-use conditions, but the context is sufficient.

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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