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build_corpus

Read-onlyIdempotent

Save a snapshot of project context to disk for reusing in LLM queries without re-running the pack pipeline.

Instructions

Pack a slice of project context into a persistent corpus on disk so future query_corpus calls can prime an LLM with the same snapshot without re-running the pack pipeline. Mutates the corpora store; returns JSON with the saved manifest. Pair with query_corpus for "ask this codebase" workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCorpus slug — alphanumeric + dash + underscore, ≤64 chars, must start with a letter or digit
scopeYesPack scope: project (whole repo), module (subdirectory), feature (NL query rank)
module_pathNoSubdirectory path when scope=module (e.g. "src/auth")
feature_queryNoNatural-language query when scope=feature (e.g. "JWT auth and refresh flow")
token_budgetNoToken budget for the packed body (default 50000)
pack_strategyNoPack strategy: most_relevant (default; feature/PageRank ranked), core_first (PageRank wins, surfaces architecturally central code), compact (signatures only — drops source bodies, lets outlines cover much more of the repo per token)
descriptionNoOptional human-readable description stored on the manifest
overwriteNoReplace an existing corpus with the same name (default false)
Behavior1/5

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

The description states 'Mutates the corpora store', which directly contradicts the annotation readOnlyHint: true. This is a serious inconsistency that misleads the agent about the tool's side effects.

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

Conciseness5/5

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

The description is two sentences with no fluff, front-loading the purpose and key behavior. Every sentence adds value.

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

Completeness4/5

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

Despite the annotation contradiction, the description covers the main purpose, mutation behavior, and return format. For a complex tool with 8 parameters and no output schema, it provides a functional overview, though additional context on overwrite behavior or disk usage could improve completeness.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no significant meaning beyond that, providing only a general usage context.

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

Purpose5/5

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

The description clearly states the verb 'pack' and the resource 'project context into a persistent corpus on disk', and distinguishes itself from siblings like query_corpus and pack_context by specifying its purpose of creating snapshots for future LLM priming.

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

Usage Guidelines3/5

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

The description mentions pairing with query_corpus for 'ask this codebase' workflows, implying a use case, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it compare with alternatives like pack_context.

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

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