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tiempor3al

learning-loop-mcp

by tiempor3al

Solutions

solutions

Retrieve a project's solutions ledger to trace solution events by revision, filter by status or solution ID, and validate verified solutions.

Instructions

Trace (append-only) of the project's solutions ledger. JSON with the list of events ordered by revision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNo
projectYes
solution_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.4.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully reveals that the data is append-only, is a JSON list, and is revision-ordered. However, it does not mention filtering behavior, pagination, or any edge conditions such as empty ledgers.

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 brief and front-loaded, with two sentences of useful information. It avoids fluff, though the first sentence is slightly awkward and the second sentence could be more precise about ordering direction.

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?

Given no annotations and no parameter descriptions in the schema, the description is incomplete for a tool with three parameters. It would need to explain parameter semantics and when to choose this over 'search' or 'register_solution' to be fully actionable.

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?

Schema description coverage is 0%, so the description must compensate by explaining the parameters. It only implicitly references the 'project' scope and says nothing about 'status' or 'solution_id'. The agent cannot infer how these optional parameters affect the returned events.

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 states that the tool provides an append-only trace of a project's solutions ledger and returns a JSON list of events ordered by revision. It is understandable as a read/query tool, though it does not explicitly distinguish itself from the sibling 'search' tool.

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?

The description gives no guidance on when to use this tool versus alternatives like 'search' or 'register_solution'. It does not state exclusions, prerequisites, or conditions that would route an agent to a sibling tool.

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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