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edit_proposal

Update a pending proposal's text or metadata while keeping its status pending.

Instructions

Update the proposed_text and/or metadata of a still-pending proposal; its status stays 'pending'.

Access level: write. Returns: JSON with the proposal_id and its status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metadataNoJSON object merged into the proposal's existing metadata.
new_textYesReplacement proposed_text (private tags are stripped before storage).
proposal_idYesThe pending_proposals id to edit.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the write access level and that the mutation preserves the 'pending' status (a non-obvious lifecycle guarantee). However, it omits permission requirements, behavior on non-pending proposals, and whether edits are recoverable.

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?

Tight and front-loaded: the core purpose leads, followed by access level and return shape in compact lines. The 'Returns' sentence is redundant given the output schema exists, costing a small amount of economy but no clarity.

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?

For a 3-parameter mutation tool with an output schema (so return values need no explanation) and a fully documented schema, the description covers purpose, scope, and access adequately. Remaining gaps are behavioral details (failure on resolved proposals, permission granularity) rather than anything blocking correct invocation.

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%, so the schema already documents new_text and metadata, establishing a baseline of 3. The description adds little beyond restating the fields, and actually refers to 'proposed_text' while the parameter is named 'new_text', a mild naming mismatch that could cause confusion.

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 and resource ('Update the proposed_text and/or metadata of a still-pending proposal') and adds the important scoping fact that status stays 'pending'. It distinguishes itself from siblings by being the only editor of an existing proposal, though it never names create/approve/reject_proposal to sharpen the boundary.

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?

The phrase 'still-pending proposal' implicitly conveys when this tool applies (and that approved/rejected proposals are out of scope), but there is no explicit when-to-use statement, no named alternative, and no guidance on what happens if the proposal is already resolved.

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