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gograph_wiki

DestructiveIdempotent

Generate a wiki directory of markdown pages from a Go codebase's static graph, covering overview, architecture, hotspots, routes, env, errors, concurrency, and API surface, to orient agents efficiently.

Instructions

Generate the llm-wiki/ directory of machine-first markdown pages from the static graph. Pages produced: overview.md, architecture.md, hotspots.md, routes.md, env.md, errors.md, concurrency.md, api-surface.md, and one packages/.md per internal package. The MCP server checks freshness before this call and refreshes in the current requested analysis mode; precise and precise_fallback graphs retry CHA/SSA after source changes. A relative output is anchored beneath the graph root and rejects linked components; an absolute output explicitly selects a local destination whose final directory must be real. Generated page paths and regular-file writes remain confined beneath the selected output root. Writes may overwrite existing regular files; MCP annotations mark it mutating and destructive. WHEN TO USE: At the start of an agent session on an unfamiliar codebase — run once to get a token-efficient orientation without issuing dozens of individual tool calls. NOT TO USE: For targeted symbol lookups (use gograph_context or gograph_source). RETURNS: JSON manifest of written page filenames and a count; error when the graph cannot be loaded or the output directory is unsafe or cannot be created.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNoWiki directory: relative paths are graph-rooted; an absolute path explicitly selects a real local output root (default 'llm-wiki')
Behavior5/5

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

Annotations already mark mutating/destructive, and the description reinforces this by disclosing that writes may overwrite existing regular files and that page paths are confined beneath the output root. It also adds freshness/retry behavior and error conditions, going beyond annotation details.

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?

The description is long but every sentence serves a purpose, covering output list, freshness, path safety, overwrite behavior, usage guidance, and returns. It is well-structured with clear labels, though it could be slightly tightened without loss.

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?

For a batch generation tool with one optional parameter and no output schema, the description provides thorough context: exact generated pages, output path rules, safety constraints, return manifest, and error cases. It also explains why to use it as an orientation tool, covering both context and alternatives.

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?

The single parameter is fully described in the schema (100% coverage), and the description restates the same semantics without adding extra nuance. Baseline 3 applies because schema carries the heavy lifting.

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 opens with a specific verb and resource: 'Generate the llm-wiki/ directory of machine-first markdown pages from the static graph.' It lists exact page outputs and differentiates itself from sibling tools by positioning as a batch orientation tool, with targeted lookups delegated to gograph_context/gograph_source.

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?

The description explicitly includes WHEN TO USE and NOT TO USE sections, prescribing use at the start of an agent session on an unfamiliar codebase and explicitly excluding targeted symbol lookups, pointing to specific sibling tools. This gives clear selection 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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