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Glama

deactivate_skill

Destructive

Deactivate an active latent skill candidate by marking it ignored and disabling its recorded native installations per host policy. Requires initialized project memory and an active latent ID.

Instructions

Mark an active latent skill candidate ignored and disable its recorded native installations according to runtime policy. Use to deactivate a latent workflow; use cleanup_skill for explicit native cleanup of a canonical skill. Requires initialized project memory and a latent ID in active state. Preserves canonical SKILL.md, but can remove native directories, replace them with disabled stubs, or preserve them according to host policy. Returns candidate and audit/snapshot references; removed directories do not necessarily have recovery snapshots. Repeating the call fails once ignored. activate_skill restores candidate state but does not reinstall native files.

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

A4.8/5.0
Behavior5/5

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

The annotations declare destructiveHint=true, idempotentHint=false, and readOnlyHint=false; the description goes well beyond by disclosing what is and isn't destroyed (canonical SKILL.md preserved; native directories may be removed, stubbed, or preserved per host policy). It also warns that removed directories may lack recovery snapshots and confirms the non-idempotent behavior ('repeating the call fails once ignored'), and names the recovery path via activate_skill.

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?

The action and its scope are front-loaded in the first sentence, and each subsequent sentence carries distinct information (alternative routing, preconditions, destruction semantics, recovery). It is dense with multi-clause sentences, but no statement is filler.

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 destructive one-parameter tool with an output schema and full annotation coverage, the description covers preconditions, policy-dependent side effects, irreversibility caveats, and the recovery tool. Nothing an agent needs before invoking it is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already defines latent_skill_id and its disambiguation from slugs and paths, setting a baseline of 3. The description adds a state constraint not in the schema ('a latent ID in active state'), which meaningfully changes parameter validity.

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 and resource ('mark an active latent skill candidate ignored and disable its recorded native installations') and immediately contrasts with the sibling cleanup_skill, which handles native cleanup of a canonical skill. The distinction between latent candidates and canonical skills is explicit, so an agent can choose between them without opening either 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?

Gives explicit when-to-use ('deactivate a latent workflow'), an explicit alternative with its condition ('use cleanup_skill for explicit native cleanup of a canonical skill'), and preconditions ('requires initialized project memory and a latent ID in active state'). It also notes the failure mode of repeating the call once ignored, which bounds usage.

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