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assess_completion

Read-only

Determines if a task meets acceptance criteria by checking fresh evidence against policy and verifying ledger integrity for trusted completion status.

Instructions

Compute completion from fresh evidence policies and ledger integrity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesIdentifier returned by create_task.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already establish that this is read-only and non-destructive, and the description is consistent with that. It adds some context by mentioning evidence policies and ledger integrity as inputs, but does not clarify what 'fresh' means or whether any implicit assumptions must hold before calling.

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 a single sentence with no filler and the core action is front-loaded. The phrase 'fresh evidence policies' is somewhat dense and jargon-heavy, which keeps it just short of maximally clear.

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

Completeness3/5

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

With one fully documented parameter and an output schema present, the structural burden is low. However, an agent still lacks enough context about when to invoke this tool relative to its siblings and what 'completion' means in this workflow.

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 schema fully describes task_id as the identifier returned by create_task, so the description does not need to add much. The description references evidence policies and ledger integrity but does not explain how task_id relates to those concepts.

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 names a specific action, 'compute completion', and references the inputs it relies on ('fresh evidence policies and ledger integrity'). However, it does not differentiate itself from siblings like execute_verification or build_proof_report, and 'completion' is left undefined.

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 given about when to call this tool versus alternatives such as prepare_verification, execute_verification, or build_proof_report. There are no preconditions, ordering hints, or exclusion criteria provided.

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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