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by paultaki

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Read-onlyIdempotent

Scan the full loop library as a digest with id, category, use_when, and verifier strength, then choose the best fit for your context.

Instructions

The entire AI Loop Library as a compact digest (~2k tokens): every loop's id, category, one-line use_when, and verifier strength. This is the highest-signal single call here — you know the operator's repo, data, and recurring pain, so scan the digest against that context and make the pick yourself. Follow with get_loop for depth or render_run_protocol to run one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoOptional exact category filter, e.g. Engineering, Growth
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds context about the output size (~2k tokens) and content, which is useful beyond annotations. No contradiction.

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?

Two sentences, no wasted words. First sentence describes output, second gives usage guidance and next steps. Perfectly front-loaded and concise.

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 simple tool (one optional param, no output schema), the description covers the main purpose, output format, and next steps. It lacks detail on how the category filter affects the digest, but overall sufficient.

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?

The input schema is self-documenting (100% coverage) with a clear description of the optional category parameter. The description does not add additional parameter information, so baseline score of 3 is appropriate.

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 it returns a compact digest of all loops with specific fields (id, category, use_when, verifier strength). This distinguishes it from siblings like search_loops (filtered) and get_loop (single item).

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

Usage Guidelines4/5

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

Explicitly says to use this as the first step ('highest-signal single call') and directs to follow up with get_loop or render_run_protocol. However, it does not explicitly state when not to use it (e.g., if you already know the exact loop id).

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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