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Guard Proposals

codapult_guard_propose

Generate evidence-based rule and contract proposals for AI agents without automatic activation, so you can review architecture guardrails before applying them.

Instructions

Generate evidence-based rule and contract proposals for an AI agent. Proposals are never activated automatically.

Input Schema

NameRequiredDescriptionDefault
rootNoProject path or workspace root.
confirmNoRequired when persist is true.
persistNoPersist proposals.json in the project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
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 discloses one genuinely important behavioral trait – proposals are never activated automatically, so this is non-destructive – but says nothing about what 'evidence-based' means, whether the tool reads the repository, whether persist triggers filesystem writes, or whether it requires review by proposal_decide.

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 sentences, front-loaded with the purpose and followed by the key safety constraint; no filler. It is arguably too terse for a tool with no annotations, but every sentence present earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter governance tool with no annotations and no output schema, and 13 closely related siblings, the description is far too thin. It omits prerequisites, what evidence is generated, the role of persist/confirm in the workflow, and how output proposals are consumed by proposal_decide.

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%, so root, confirm and persist are already documented, including the dependency that confirm is required when persist is true. The description adds no parameter-level meaning beyond the schema, so the baseline of 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 and resource: 'Generate evidence-based rule and contract proposals for an AI agent.' That is clear and identifiable, but the description never distinguishes it from the numerous sibling governance tools (proposal_decide, verify, analyze, check) that also touch rules and proposals.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance. It never says whether to call this before proposal_decide, whether init must run first, or what prerequisites (e.g., project root, evidence sources) exist. Only the implicit reading of the name suggests its place in the workflow.

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