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Awareness — Memory, Knowledge & Agent Markets

awareness_mark_skill_used

Mark a skill as used and report the outcome.

Call this AFTER applying a skill's instructions during a task.
Outcome feedback closes the learning loop:
- "success" (default): full decay reset, confidence boost
- "partial": partial decay boost, no confidence change
- "failed": decay & confidence decrease; 3+ consecutive failures → needs_review

Args:
    skill_id: The skill ID to mark as used.
    outcome: "success" (default), "partial", or "failed".
    memory_id: Target memory id (auto-resolved if omitted).
    api_key: Bearer token for authentication.

Input Schema

NameRequiredDescriptionDefault
api_keyNo
outcomeNosuccess
skill_idYes
memory_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses the state effects of each outcome value (decay reset vs. partial boost vs. decay and confidence decrease), the escalation rule (3+ consecutive failures to needs_review), the auto-resolution behavior of memory_id, and the fact that api_key is a Bearer auth token.

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 purpose and timing, then outcome semantics, with no filler prose. The closing Args block restates field names the schema already carries, which is mildly redundant, though it earns its place by supplying the missing semantic detail.

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 4-parameter mutation with no annotations and no output schema, the description covers purpose, timing, per-outcome effects, escalation threshold, and auth. It stops short of describing what the call returns or how repeated calls behave, which an agent finishing the loop might want to know.

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

Parameters5/5

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

Schema coverage is 0%, so the description must supply all parameter meaning, and it does: skill_id is the target, the outcome enum ('success'|'partial'|'failed') and its default are defined only here (the schema has no enum and no descriptions), memory_id is documented as auto-resolved when omitted, and api_key is identified as a Bearer token.

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 a skill as used and report the outcome'), which is operationally distinct from the sibling awareness_apply_skill (which applies the skill). An agent can tell from the first line alone which of the two it needs.

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

Usage Guidelines4/5

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

Gives explicit sequencing guidance ('Call this AFTER applying a skill's instructions during a task'), which tells the agent when in the workflow to invoke it. It never names the alternative sibling (awareness_apply_skill) nor states when not to call it, so it stops short of full routing guidance.

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

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