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squatch-c-c

squatch-codebook-mcp

by squatch-c-c

codebook_analogy

Find the best completion for an analogy a:b::c:? by searching your notes using hyperdimensional computing.

Instructions

Analogy a:b :: c:? over your notes (VSA transform), returns the best completions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notes_dirYes
aYes
bYes
cYes
globNo*.md
kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions 'VSA transform' (suggesting vector operations) and 'returns the best completions,' but does not state whether the tool is read-only, requires specific permissions, or has side effects. The absence of any disclosure about destructive behavior or resource usage leaves the agent uncertain.

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

Conciseness4/5

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

The description is very concise—a single sentence with no superfluous words. However, it could be slightly restructured to first state the verb and then the pattern; still, no wasted text.

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

Completeness2/5

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

Despite having an output schema (not shown), the description lacks essential context for a 6-parameter tool. It does not explain the analogy task's prerequisites, the role of notes_dir and glob, or the nature of 'best completions.' The agent would need additional information to use the tool effectively.

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

Parameters2/5

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

The input schema has 0% parameter description coverage, so the description must fill the gap. It only references a, b, c in the analogy pattern but does not define them, nor does it explain notes_dir, glob, or k. The agent is left to infer that a, b, c are strings and that k controls the number of results, but this is not explicit.

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

Purpose4/5

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

The description clearly identifies the tool's purpose: solving analogies in the form a:b::c:? using a VSA transform on notes. It mentions returning the best completions, which distinguishes it from sibling tools like codebook_neighbors (finding neighbors) or codebook_query (general queries). However, it could be more explicit about the output format or that it returns multiple candidates.

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?

No guidance is provided on when to use this tool versus alternatives like codebook_related or codebook_walk. The description does not specify prerequisites, limitations, or typical use cases. An agent would not know if this tool is for semantic analogies or simple string matching, or when to prefer it over other retrieval methods.

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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