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sassy_hooks_suggest

Suggests relevant hooks based on the user's request text, returning ranked matches to resolve uncertainty about which hook to use.

Instructions

Suggest hooks based on what the user is trying to do.

Pass the user's request text. Returns matching hooks ranked by relevance. The AI should call this when it's unsure which hook to use, or proactively when the user's request matches a known domain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It states that the tool 'Returns matching hooks ranked by relevance', which implies read-only behavior and gives insight into the output format. It does not mention edge cases or permissions, but for a non-mutating suggestion tool, the key behavioral trait (returning ranked results) is disclosed.

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 three sentences, front-loaded with the main action, and every sentence adds value: purpose, input/output, and usage guidance. There is no redundancy or unnecessary detail.

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

Completeness5/5

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

For a simple single-parameter tool with an output schema, the description covers the essential aspects: what it does, what input to provide, what output to expect (ranked suggestions), and when to invoke it. The existence of an output schema covers return-value details, so the description is sufficiently complete for an agent to use it correctly.

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

Parameters4/5

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

The input schema provides only a parameter name ('user_text') with no description (0% schema coverage). The description compensates by explaining 'Pass the user's request text', giving clear semantic meaning. It does not provide format details or examples, but the single simple string parameter is adequately explained.

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 tool's function with a specific verb ('Suggest') and resource ('hooks'), and adds the scope 'based on what the user is trying to do'. It distinguishes itself from sibling hook tools like list/activate/deactivate by emphasizing ranked matching, making its unique 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 Guidelines4/5

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

The description explicitly specifies when to use this tool: 'when it's unsure which hook to use' and proactively when the request matches a known domain. However, it does not name alternative tools (e.g., sassy_hooks_list, sassy_hooks_activate) or state when not to use it, so it falls short of a full 5.

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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