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View a rollup of store sizes, autonomous loop activity, and outputs such as skills materialized and candidate statuses. Identify loops that fire without producing results or pending backlogs.

Instructions

One-call rollup of the whole thread-keeper system: store sizes, how often each autonomous loop fired (in the last window_days and 30d), and what those loops actually produced (skills materialized, candidates accepted vs rejected, tier promotions). Read-only; no spawn, no mutate.

Use to see system health at a glance, spot loops that fire but produce nothing (e.g. shadow_review passes >> skills materialized), or a backlog building up (e.g. extract_candidates pending climbing).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
window_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description bears full burden. It discloses the tool is read-only and describes what data it aggregates. It provides useful behavioral context beyond the schema.

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?

The description is two sentences, front-loaded with the purpose, then provides concrete examples. Every sentence adds value with no waste.

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?

With one simple parameter and an output schema (not shown but present), the description is complete. It covers what the tool does, what it provides, and usage context.

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

Parameters4/5

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. It adds meaning for the single parameter 'window_days' by explaining it controls the time window for loop frequency. This is explicit and helpful.

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 the tool provides a 'one-call rollup of the whole thread-keeper system' and lists specific metrics (store sizes, loop frequency, production outcomes). It distinguishes from siblings by noting it is read-only and does not spawn or mutate.

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?

The description explicitly states 'read-only; no spawn, no mutate' and gives concrete examples of when to use it (system health glance, spotting unproductive loops, backlog buildup). However, it does not explicitly mention when not to use it or suggest alternative tools.

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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