Search the AskAgent archive of real, working fixes by error string. Paste the exact error from a stack trace or log (symptom words also work). Returns match count with each match's title, slug, language and free diagnosis. Call this on every unexplained error before debugging from scratch.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The error string or symptom, e.g. "RangeError: Invalid time value" |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It clearly states the return shape (match count, title, slug, language, free diagnosis) and implies a safe, read-only search operation. It does not mention rate limits, authentication, or empty-result behavior, but for a simple search tool the description is informative.
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 three focused sentences with no filler. It front-loads the action, then gives usage detail, return info, and a clear directive, with every sentence adding value.
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?
The tool is simple: one required parameter and no output schema. The description explains what to pass, how to pass it, what the response contains, and when the tool should be used. Nothing essential is missing for an agent to call it correctly.
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 baseline is 3. The description adds meaningful practical guidance beyond the schema: paste the exact error from a stack trace or log, and symptom words are acceptable substitutes. This helps the agent phrase the query correctly.
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 names a specific verb ('Search'), a specific resource ('AskAgent archive of real, working fixes'), and the primary input ('error string'), which makes the tool's purpose unmistakable and distinguishes it from sibling tools like get_fix or list_samples.
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?
It gives explicit when-to-use guidance: 'Call this on every unexplained error before debugging from scratch.' It also advises pasting the exact error and notes that symptom words work. It does not explicitly discuss alternatives or when not to use this tool, so it stops short of a 5.
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 clearly distinct role: search_fixes finds matches, get_fix retrieves a specific fix by slug, and list_samples shows example fixes. There is no realistic confusion between the three tools.
All tool names follow a consistent verb_noun snake_case pattern: search_fixes, get_fix, and list_samples. The naming is predictable and easy for an agent to reason about.
Three tools is well-scoped for a focused read-only fix archive. Each tool earns its place and together they support a minimal search-to-retrieval workflow.
The domain is a read-only consumer-facing archive, and the tool surface covers discovery via search, preview via samples, and full retrieval via get_fix. There are no obvious dead ends or missing operations for the stated purpose.