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wiki.lint

Identify orphan entries, broken links, stale sources, and missing cross-references in your wiki. Switch to semantic mode for LLM-driven contradiction and gap analysis.

Instructions

Health-check the wiki: find orphan entries, broken links, stale sources, and missing cross-references. Use lint_mode='semantic' to get an LLM-ready payload for deeper analysis (contradictions, stale claims, missing entity pages, missing cross-references).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lint_modeNostructural (default): orphans, broken links, stale sources. semantic: returns gathered KB/memory data + a prompt for LLM-driven contradiction and gap analysis.
project_idNo
project_rootNo
max_kb_entriesNoMax KB entries to include in semantic payload (default 50, max 200)
max_memory_entriesNoMax memory entries to include in semantic payload (default 50, max 200)
content_preview_lengthNoCharacters of content to include per entry in semantic payload (default 500)
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that the tool checks for specific issues and returns either a structural report or a semantic payload (KB/memory data + prompt). However, it does not mention if the tool writes or modifies anything, rate limits, or required authentication. The behavioral description is adequate but lacks depth.

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 two sentences, front-loading the core purpose and then detailing the semantic mode. Every sentence adds value, though it could be slightly more compact by omitting the redundant 'missing cross-references' mention (appears twice). Overall, it is well-structured and efficient.

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

Completeness3/5

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

Given the complexity (6 parameters, two modes, no output schema), the description covers the main modes and their outputs but lacks guidance on required parameters, error conditions, or what happens if project_id/project_root are missing. The absence of an output schema means the description should clarify return values more explicitly.

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 description coverage is 67% (4 of 6 parameters described). The description adds meaning beyond the schema by explaining what each lint_mode produces and hinting that project_id/project_root are likely needed. However, the schema already describes parameters well (enum for lint_mode, defaults for max_kb_entries, etc.), so the description provides moderate added value.

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 clearly states the tool performs a health-check of the wiki, listing specific issues it finds (orphan entries, broken links, stale sources, missing cross-references). It also distinguishes two modes, 'structural' and 'semantic', with clear purpose for each. This is a specific verb+resource combination that differentiates from siblings like wiki.export or health.check.

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

Usage Guidelines3/5

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

The description explains when to use each lint_mode (structural for basic checks, semantic for deeper LLM analysis) but does not explicitly state when not to use this tool or suggest alternatives. It provides context for the semantic mode but lacks guidance on prerequisites (e.g., project_id or project_root needed).

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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