Skip to main content
Glama
paultaki
by paultaki

search_loops

Read-onlyIdempotent

Find bounded, verifiable work loops in AI Loop Library by job-to-be-done, keyword, or category. Get ranked matches with a one-line why-matched to choose the right loop for an agent.

Instructions

Search AI Loop Library's bounded, verifiable work loops by job-to-be-done, keyword, or category. Each loop ships with a trigger, one-change-per-round discipline, a verification check, a stop condition, a budget, and a human approval boundary — so an agent can run it without thrashing. Returns ranked matches with a one-line why-matched.

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYesJob to be done or keywords, e.g. 'flaky tests' or 'source-check a draft'
categoryNoOptional exact category filter, e.g. Engineering, Knowledge, Operations

Output Schema

NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.1.0
    • addedInput schema / additionalProperties
      Added value: +false
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "results": {
      +      "items": {
      +        "properties": {
      +          "category": {
      +            "type": "string"
      +          },
      +          "id": {
      +            "type": "string"
      +          },
      +          "summary": {
      +            "type": "string"
      +          },
      +          "title": {
      +            "type": "string"
      +          },
      +          "url": {
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "id",
      +          "title",
      +          "category",
      +          "url",
      +          "summary"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "results"
      +  ],
      +  "type": "object"
      +}
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint), and the description adds real behavioral context: loops are bounded, ship with trigger/verification/stop-condition/budget/human-approval boundaries, and results are ranked with a one-line why-matched. It omits pagination/rate-limit behavior, keeping it below 5.

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?

Front-loaded with the verb and resource, then one compact sentence explaining what a loop contains. It is a touch long in the middle clause list, but every phrase carries informational weight about the returned objects.

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?

An output schema exists, so return values need not be explained, yet the description still tells the agent results are ranked and include a why-matched line. For a low-risk read-only search with three params, nothing critical is missing.

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?

Schema coverage is 67% and the schema already documents query and category with examples. The description reinforces the 'job-to-be-done' framing and confirms category filtering but adds no syntax, matching, or limit semantics beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb (Search) and resource (AI Loop Library's bounded, verifiable work loops) plus the search axes (job-to-be-done, keyword, category), so it is distinguishable from get_loop or browse_catalog. It does not explicitly name rival siblings like pick_loop_for_goal, so it stops short of a 5.

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

Usage Guidelines3/5

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

Usage is implied by the query axes, but there is no explicit when-to-use statement, when-not condition, or named alternative. The closest sibling, pick_loop_for_goal, is also goal-driven and the description gives no cue for choosing between them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.