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mark_complete

Marks a task as complete using its ID or name. If unsure, fuzzy-matches the task name to mark it done.

Instructions

Mark a task as done. Use this when the user says 'done', 'finished', 'crossed that off', or anything that means they completed something. Fuzzy-match the name first with check_tasks if you're not sure of the exact ID. Celebrate appropriately — one line is enough.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoThe task ID to mark complete.
nameNoTask name to fuzzy-match if you don't have the ID.
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states that it marks a task as done and suggests celebrating, but does not disclose potential side effects (e.g., irreversible action? requires write permissions?), prerequisites, or how task state changes. Minimal behavioral context beyond the obvious.

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?

Three sentences, each front-loaded with key info: purpose, usage trigger, and a brief behavior note. The celebration remark is slightly extraneous but harmless. No filler, but could be tightened.

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?

For a simple mutation tool with 2 parameters and no output schema, the description covers the core use case, when to use it, and how to resolve ambiguity. It does not describe return values, but that is acceptable given the lack of output schema. Minor missing info on success/failure indicators.

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 coverage is 100%, and the description adds significant value: it explains the purpose of each parameter (id vs name for fuzzy-matching) and suggests using check_tasks to find the correct ID. This goes beyond the schema's own descriptions.

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 'Mark a task as done' and provides specific trigger phrases (done, finished, crossed that off). It explicitly distinguishes itself from sibling tools like mark_incomplete and gives context for when to use it.

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?

Explicit when-to-use guidance is given (user says completion phrases) and a pre-step is recommended (fuzzy-match with check_tasks). It does not explicitly mention when not to use, but the positive guidance is clear and actionable.

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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