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activate_skill

Reactivate an ignored latent skill candidate while its SKILL.md and valid frontmatter remain, restoring active status with audit references. Reverses candidate deactivation, not native file reinstall.

Instructions

Reactivate an ignored latent skill candidate whose generated SKILL.md still exists and has valid frontmatter. Use to reverse candidate deactivation; use create_skill or publish_skill for canonical creation. Requires initialized project memory and a latent candidate ID in ignored state. Updates latent status with audit/snapshot references; it does not reinstall removed native files. Returns the candidate, skill_file, and mutation references. Use sync_skills separately for native copies where applicable; repeating activation fails once the candidate is active.

Input Schema

NameRequiredDescriptionDefault
latent_skill_idYesExact latent candidate ID returned by track_latent_skill, list_skills, or recommend_skills; not a canonical skill slug or file path.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.4
    • addedInput schema / properties / latent_skill_id / description
      Added value: +"Exact latent candidate ID returned by track_latent_skill, list_skills, or recommend_skills; not a canonical skill slug or file path."
  2. First observedv0.4.0

TDQS

A4.4/5.0
Behavior4/5

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

Goes well beyond the annotations by disclosing preconditions (initialized project memory, candidate must be in ignored state), that it writes latent status with audit/snapshot references, that it does not reinstall removed native files, and that repeat activation fails once active — consistent with idempotentHint=false. The only weak spot is that the return-value sentence overlaps the output schema rather than adding new behavioral detail.

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 action and its preconditions, and nearly every clause carries distinct information (alternatives, preconditions, non-effects, failure mode). The sentence enumerating return values ('Returns the candidate, skill_file, and mutation references') is largely redundant given the output schema.

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?

For a single-parameter mutation with an output schema, the description supplies everything an agent needs: entry preconditions, alternatives, side effects on latent status, what it explicitly does not do, and repeat-call behavior. No meaningful gap remains.

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 the schema already explains that latent_skill_id is the exact candidate ID, not a canonical slug or file path. The description adds no parameter-level detail beyond that, 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 ('reactivate') and a precisely scoped resource ('an ignored latent skill candidate whose generated SKILL.md still exists and has valid frontmatter'). It explicitly distinguishes itself from create_skill, publish_skill, and sync_skills, so an agent can select it 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 Guidelines5/5

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

Explicitly names when to use it ('to reverse candidate deactivation'), which siblings to use instead for canonical creation (create_skill, publish_skill) and native copies (sync_skills), and the failure condition for repeated calls. Nothing about routing is left to inference.

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