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identify_project

Identify the most relevant project from a text snippet by scoring it against your project corpus. Use this to route queries to the correct project context before responding.

Instructions

Score a text snippet against the indexed project corpus and return the best-match project.

Returns the top project ID, a confidence score (0.0-1.0), and the next two runners-up.

USE WHEN: the user pastes a question or note and you need to route it to the right project's context before answering. NOT FOR: detecting the user's CURRENT project — use get_active_project, which factors in CWD and window title.

BEHAVIOR: pure read; runs TF-IDF + project-keyword scoring. No side effects.

PARAMETERS: text: snippet to classify. Required, non-empty. Longer text scores more reliably; aim for 50+ characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, but description fully covers behavior: declares 'pure read', describes algorithm (TF-IDF + project-keyword scoring), and states no side effects.

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?

Well structured with separate sections for output, usage conditions, behavior, and parameters. No extraneous text; every sentence adds value.

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?

Given output schema exists, description still covers return values. Parameter guidance and behavioral context are fully addressed. Complex classification use case is well specified.

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

Parameters5/5

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

Schema has 0% description coverage, but description compensates fully: states parameter is required, non-empty, and gives length recommendation (50+ characters for reliability). Adds substantial value.

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?

Clearly states it scores text against project corpus and returns best-match project with top ID, confidence, and runners-up. Explicitly differentiates from sibling get_active_project by stating NOT FOR detecting current project.

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

Usage Guidelines5/5

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

Provides explicit USE WHEN (routing user's text to right project context) and NOT FOR (detecting current project) with named alternative (get_active_project). Gives clear decision logic.

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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