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antientropy_grep

Search nonprofit governance and compliance articles using regex patterns to find specific content across 140+ resources with formatted results.

Instructions

Search article content with a regex pattern.

Returns matches formatted like ripgrep: slug:line_number:matching_line

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patternYes
case_insensitiveNo
context_linesNo
head_limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context by describing the return format ('Returns matches formatted like ripgrep: slug:line_number:matching_line'), which is useful. However, it doesn't cover other behavioral aspects like error handling, performance implications, or any constraints beyond the output format, leaving gaps in transparency.

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 front-loaded with the core purpose in the first sentence and adds necessary output format details in the second. Every sentence earns its place without redundancy, making it efficient and well-structured for quick understanding.

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?

Given the tool's complexity (4 parameters, 0% schema coverage, no annotations) and the presence of an output schema, the description is reasonably complete. It explains the purpose and output format, but could improve by addressing parameter semantics and usage guidelines to better compensate for the lack of annotations and low schema coverage.

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 0%, so the description must compensate, but it provides no information about parameters beyond implying a regex pattern. The description mentions 'regex pattern' which aligns with the 'pattern' parameter, but doesn't explain the semantics of 'case_insensitive', 'context_lines', or 'head_limit'. This partial compensation results in a baseline score due to the lack of detailed parameter guidance.

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 specific action ('Search article content') and the method ('with a regex pattern'), distinguishing it from siblings like antientropy_categories, antientropy_glob, and antientropy_read. It provides a verb+resource combination that is precise and unambiguous.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus its siblings, such as antientropy_glob or antientropy_read. It lacks explicit context, exclusions, or alternatives, leaving the agent to infer usage based on tool names alone without any direction.

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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