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pack_context

Bundle key source files into a token-limited markdown pack for LLM context, prioritizing paths that match focus keywords.

Instructions

Pack a token-budgeted markdown bundle of the most relevant source files for an LLM. Prefer entrypoints and paths matching focus keywords.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNoRepository root. Defaults to REPO_CONTEXT_ROOT or cwd.
focusNoKeywords or path fragments to prioritize (e.g. ['auth', 'src/api']).
max_filesNoMaximum files to include (default 40).
max_tokensNoApproximate token budget (default 12000).
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral transparency burden. It discloses selection behavior ('most relevant', 'prefer entrypoints and paths matching focus keywords') but does not mention side effects, output delivery mechanism, or whether it is purely read-only. This gives some insight but leaves operational traits unspecified.

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, front-loaded with the core action, and contains no filler or redundant information. Every word earns its place, making it an exemplary model of conciseness.

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?

With no output schema, the description should clarify the return value and any I/O behavior. It explains the output concept ('markdown bundle') but does not specify whether the bundle is returned directly, written to a file, or delivered via stdout. For a tool with four documented parameters and a clear purpose, this is a minor gap; the overall picture is complete enough for most agents.

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 coverage is 100%, so the parameters are already well-documented in the schema. The description's mention of 'focus keywords' simply maps to the 'focus' parameter without adding new semantic details or clarifying interactions between parameters, keeping this at the baseline.

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 a specific action ('Pack') and resource ('source files') with an outcome ('token-budgeted markdown bundle'). It distinguishes itself from siblings (repo_map, search_code) by focusing on bundling relevant files rather than mapping or searching, making the tool's purpose unambiguous.

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 implies usage ('for an LLM') but does not explicitly state when to use this tool versus alternatives or include exclusions. The 'focus keywords' hint is input guidance, not tool-selection guidance, so there is no clear context for sidetracking to sibling tools.

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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