fact_check_document

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

With no annotations, the description carries the full burden. It discloses the use of local LLM and free sources, and the output categories. However, it does not mention that auto_fix modifies the file, potential side effects, error handling, or resource usage, which would be valuable for safe invocation.

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

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

The description is a single, front-loaded sentence that immediately conveys the tool's core action, target, and output. Every word is necessary and there is no redundancy.

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

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

Given the tool's moderate complexity (3 params, no output schema, no annotations), the description is adequate but not complete. It lacks details on return format, error scenarios, and any integration with sibling tools (e.g., how results feed into add_citations or git_commit_corrections).

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

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 adds no new parameter context beyond the schema's own descriptions. The baseline of 3 is appropriate, as the schema already explains the parameters adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: fact-checking a Markdown/Obsidian note using local LLM and free sources, and identifies claim statuses. It distinguishes from sibling tools like verify_claim (single claim) and scan_vault_for_issues (broader scanning).

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

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

The description gives no explicit guidance on when to use this tool versus siblings (e.g., verify_claim for individual claims). It does not mention prerequisites or scenarios where this tool is inappropriate, leaving the agent to infer from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.