myco_molt

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

No annotations are provided, so the description carries the full burden. It discloses side effects (writes to _canon.yaml and changelog), dry-run behavior ('prints the diff'), and version refusal ('down-bumps are refused unless --allow-downgrade is passed at the bump_version.py layer'). It also describes the return object fields, compensating for the lack of an output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with four distinct paragraphs covering purpose, usage, side effects, and return values. It is front-loaded with the main action. While it is somewhat lengthy, every sentence adds value, so it earns a 4 for being appropriately sized and organized.

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

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

Given the tool's moderate complexity (multiple file writes, version constraints) and the absence of an output schema, the description provides sufficient context: it explains the atomic operation, dry-run preview, return fields, and error conditions (down-bump refusal). It is complete enough for an agent to execute correctly.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions. The tool description adds no new per-parameter detail beyond what the schema already provides (e.g., contract format, dry_run default). Thus, the description provides marginal added value for parameter semantics, earning the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's core function: 'Ship a contract-version bump' by updating specific fields in _canon.yaml and docs/contract_changelog.md, and advancing a counter. It specifies the verb ('ship'), resource ('contract version'), and distinguishes itself from sibling tools (e.g., myco_assimilate, myco_brief) through unique release-time version management.

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

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

The description provides explicit when-to-use guidance: 'AT RELEASE TIME, not during development.' It also specifies when not to use ('Do NOT call this mid-session') and mentions an orchestrating companion (bump_version.py) and an alternative (skip-molt option). This clearly helps an agent choose this tool over alternatives.

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