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compare_governance_outcomes

Read-onlyIdempotent

Aggregate governance throughput over a window: CIPs that changed status (approved / rejected / advanced), counts of cip-vote and cip-discuss mailing activity, and dev-fund proposals opened in the window that are closed today (merged, withdrawn and rejected are not distinguished; no close dates are stored). Canton-specific. Use to summarise "what governance has shipped this quarter?".

Input Schema

NameRequiredDescriptionDefault
window_daysNoWindow in days, 7-365 (default 90).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Changed3 schema fields changed
    • addedInput schema / properties / window_days / default
      Added value: +90
    • changedInput schema / properties / window_days / description
      Previous value: -"Window in days, 7-365."New value: +"Window in days, 7-365 (default 90)."
    • removedInput schema / required
      Removed value: -[
      -  "window_days"
      -]
  3. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add semantics. It does that by disclosing a non-obvious data limitation: merged/withdrawn/rejected outcomes are not distinguished and no close dates are stored, which directly affects how results must be interpreted.

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 scope, and every clause contributes (metrics list, limitation caveat, domain scope, use case). It is a single heavily nested sentence near the upper limit of comfortable density, but nothing is padding.

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?

No output schema exists, so the description must describe return content, and it does by naming each aggregate it produces. Combined with the caveat about undistinguished close outcomes and the Canton scope, an agent has enough to call it and to interpret the result.

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 description coverage is 100% and window_days already documents its 7-365 range and default of 90. The description only says aggregation happens 'over a window' without adding syntax or edge-case behavior beyond the schema, so the baseline 3 applies.

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?

States a specific verb (aggregate) and resource (governance throughput) and then enumerates the exact metrics produced: CIP status changes, cip-vote/cip-discuss mailing volume, and dev-fund proposals. This lets an agent separate it from per-item siblings such as get_cip_history, list_governance_votes, and get_dev_fund_activity without opening any schema.

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?

Provides a concrete triggering question ('what governance has shipped this quarter?') and scopes itself as Canton-specific, which is real usage context. However, it names no alternative tool and gives no explicit when-not-to-use guidance, so it stops short of full routing.

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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