Use when: search_solutions returned count > 0 and you applied a returned solution that fixed the problem — call this with record_usage_solution_id (or the id you used) before ending the task. Returns: updated usage count for the solution. Do not use when: results did not help, you have not tried the fix yet, or you are posting new content.
| Name | Required | Description | Default |
|---|---|---|---|
| solution_id | Yes | ID of the solution to record usage for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate mutation (readOnlyHint false) but the description adds context by stating the exact action (recording usage), the return value (updated usage count), and the timing (before ending the task). It goes beyond the annotations without contradicting them.
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 compact and efficiently structured: a 'Use when' trigger, a return value, and a 'Do not use when' exclusion. Three sentences, no wasted information, with the most important condition front-loaded.
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?
For a single-parameter tool with no output schema, the description provides all necessary context: when to call, what to return, and explicit exclusions. Nothing critical is missing.
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?
The schema covers the parameter with 'ID of the solution to record usage for', and the description adds minimal extra context by advising to use the id from search_solutions. However, the description misnames the parameter as 'record_usage_solution_id', which could confuse an agent. Baseline 3 due to high schema coverage.
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 records usage for a solution, with a specific trigger condition and return value. However, it refers to a parameter as 'record_usage_solution_id' instead of the actual 'solution_id', which introduces minor confusion.
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?
Provides explicit when-to-use ('search_solutions returned count > 0 and you applied a returned solution that fixed the problem') and when-not-to-use conditions ('results did not help, you have not tried the fix yet, or you are posting new content'). This fully distinguishes when the tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: adding addenda vs. editing core solutions vs. submitting new solutions vs. filing issues vs. searching, etc. There is no overlap; the descriptions clearly differentiate when to use each tool.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., add_addendum, search_solutions). The verbs are descriptive and the structure is uniform, making it predictable for an agent.
With 9 tools, the server is well-scoped for a solution and issue management domain. Each tool serves a needed function without redundancy or bloat, covering the core workflows adequately.
The tool surface covers creation, reading, updating (via suggest_edit and add_addendum), and a reporting mechanism for problematic content. File submission and issue resolution are included, but there is no explicit tool for deletion or archival, which is a minor gap.