Reads massive directories or 100k+ line logs and condenses them into AST code blocks and pinpointed issue context, so you can find the relevant code fast.
Reads massive directories or 100k+ line logs and distills down to AST code blocks and pinpointed issue context.
| Name | Required | Description | Default |
|---|---|---|---|
| directory_or_log | Yes | ||
| issue_description | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.6.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It implies a read-only extraction ('reads... distills'), which is useful, but says nothing about cost/latency for 100k+ line inputs, whether there are size or path restrictions, whether results are cached, or what happens on unreadable paths. For a tool that ingests very large inputs, that is a meaningful gap.
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?
A single front-loaded sentence that states the input scale and the output shape with no filler. It is efficient, though it is arguably too terse given the undocumented parameters.
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?
An output schema exists, so return values need not be explained. But with zero annotation coverage and 0% schema description coverage, the agent is left without knowing input format conventions or operational constraints for a tool that processes very large inputs — the two areas the description should have closed.
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 0% — both parameters have only titles and no descriptions. The description implies 'directory_or_log' is a path or raw log and 'issue_description' is a question, but it does not clarify format (absolute path? glob? inline content?) or how the issue description shapes the distillation. The description does not compensate for the schema gap.
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?
Names a specific verb pair (reads/distills) and concrete resources (massive directories, 100k+ line logs), plus the output form (AST code blocks, pinpointed issue context). An agent can tell this is a context-reduction/extraction tool rather than a task runner or verifier like most siblings. It stops short of explicitly distinguishing itself from the nearest sibling (e.g., call_codex_architect) that might also analyze code.
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 phrases 'massive directories' and '100k+ line logs' imply a size threshold for when the tool is appropriate, which is a usable trigger. However, there is no explicit when-not-to-use guidance, no statement about small inputs, and no reference to any alternative sibling tool for context gathering.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.