Statically identifies root-cause candidate functions, methods, and classes from an issue description or traceback to help pinpoint bug locations in a repository.
Statically identify root-cause candidate functions, methods, and classes from an issue description or traceback in <2 ms.
| Name | Required | Description | Default |
|---|---|---|---|
| issue | Yes | Bug description or error traceback | |
| repo_path | Yes | Path to repository root |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations supplied, the description carries the burden, and 'statically' usefully signals that no code is executed and behavior is read-only. However it says nothing about output format, ranking/confidence of candidates, limits on result count, or whether the repo is modified, and the '<2 ms' latency claim is the only additional behavioral detail.
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?
One sentence, front-loaded with the verb and resource, with the input source and performance claim appended. Nothing is redundant or buried.
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 simple two-required-parameter tool with no output schema, the description conveys what kind of entities come back (candidate functions, methods, classes), which is the key missing piece an agent would need. It lacks detail on result ordering or size, but that is a modest gap at this complexity level.
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 description coverage is 100%, so both parameters are already documented. The description only reinforces that the issue input may be a plain bug description or an error traceback, which is marginal added meaning; the baseline of 3 is appropriate.
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 ('statically identify') and a concrete output set (root-cause candidate functions, methods, and classes) plus the input form (issue description or traceback), so an agent immediately knows what the tool produces. It does not explicitly contrast itself with siblings like neurocode_slice or neurocode_repair_ollama, which keeps it short of a 5.
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?
Usage is implied by the input contract: call it when you have a bug description or traceback and a repo path. There is no explicit statement of when to prefer this over neurocode_slice or neurocode_repair_ollama, and no exclusions or prerequisites are given, so the agent must infer routing from the single sentence.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.