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sheepit-mcp

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by sheepit-ai

List releases that regressed

release_regressions

List releases with significant crash-free rate drops, optionally filtered by environment or since a timestamp, to detect regressions in deployments.

Instructions

List releases that REGRESSED (crash-free rate dropped past the server's significance gate), newest-first, optionally since a timestamp. kind='release' means the release degraded vs the prior release; kind='change' means it degraded right after a specific flag/config change (see change_entity_key). The drop is detected server-side — report crash_free_delta as given, do not recompute it. crash_free_delta of 0 on a kind='change' entry may mean the delta was not computable — check pre/post_crash_free_rate to confirm before treating 0 as a true no-change reading. Use release_health(release_id) to investigate a specific regression in depth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoISO timestamp lower bound. Defaults to 24 h ago.
environment_idNoFilter regressions to one environment.
limitNoMax regressions to return (1-100).
Behavior4/5

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

With no annotations, description fully handles transparency: states regression detection is server-side, crash_free_delta is not recomputed, and how to interpret 0 values (non-computable). Provides guidance on confirming via pre/post rates. No contradictions.

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?

Two well-structured paragraphs: first sentence gives purpose, second provides behavioral details. Every sentence adds value. Slightly verbose in second paragraph but overall effective.

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?

Given 3 parameters and no output schema, description covers key behavioral concepts (kinds, delta interpretation) adequately. Could mention output structure but not required. Complete for a list tool.

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 100% with clear descriptions for each param (since, environment_id, limit). Description adds minimal extra context (e.g., 'optionally since a timestamp'). Baseline 3 is appropriate.

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?

Clearly states 'List releases that REGRESSED' with specific filtering and ordering (newest-first). Distinguishes from siblings like release_list (general list) and release_health (in-depth investigation) by purpose and detail.

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?

Explains when to use (to list regressed releases, optionally with timestamp), describes meaning of kind='release' vs 'change', and recommends release_health for deeper investigation. Lacks explicit when-not-to-use but context is sufficient.

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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