retract_skillRetract a previously promoted skill. Sets the Engine artifact's living status to 'retracted', removing it from future retrieval results. Use when a skill is found to be incorrect or outdated.
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | Additional notes | |
| reason | Yes | Reason for retraction | |
| submission_id | Yes | ID of the skill submission to retract |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It discloses the key behavioral trait: setting living status to 'retracted' and removing the skill from future retrieval results. However, it does not mention prerequisites (e.g., whether the skill must exist), failure modes, reversibility, or permission requirements, leaving gaps in full behavioral transparency.
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 two sentences long, front-loaded with the action verb, and contains no redundant phrasing. Every sentence adds value: first states the action, second explains the effect and usage scenario. Excellent conciseness.
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?
The tool has moderate complexity with 3 parameters, a schema with 100% description coverage, and an output schema. The description covers the core purpose, the behavioral effect, and the recommended use case. It does not detail edge cases or errors, but given the schema and output schema richness, it is sufficiently complete for an agent to select and invoke the tool 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?
The schema covers 100% of the parameters with descriptive text (submission_id, reason, notes), so the baseline is 3. The description adds no additional parameter-level meaning beyond the schema, so no credit beyond baseline is warranted.
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 starts with a specific verb+resource: 'Retract a previously promoted skill.' It also explains the effect: 'Sets the Engine artifact's living status to 'retracted', removing it from future retrieval results.' This clearly distinguishes it from siblings like dismiss_skill (which may apply pre-promotion) and promote_skill (the inverse action).
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 a clear usage condition: 'Use when a skill is found to be incorrect or outdated.' It also implicitly constrains usage to previously promoted skills, distinguishing from non-promoted submissions. However, it does not explicitly name alternatives or state when not to use, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping purposes: check_claim and memory_claim_check are the same function with different tiers, get_freshness_report and memory_freshness_report are duplicates, get_correction_chain and compare_versions both trace history, and investigate_question subsumes many other retrieval tools. This will cause agent misselection.
Most tools follow a verb_noun pattern (get_constraints, declare_constraint, sync_pull, etc.). Exceptions like memory_claim_check, memory_freshness_report, session_debrief, and verify_before_acting deviate but are relatively few. Overall the naming is readable and mostly predictable.
75 tools is excessive for a memory server. Many are highly niche or direct duplicates (e.g., paid/free versions of the same function). The count far exceeds typical well-scoped servers and introduces cognitive overhead without proportional value.
The server covers a wide array of memory, constraint, decision, skill, and sync operations, which is impressive. However, there are notable gaps: no direct delete or edit for memory facts (only corrections/versioning), and no bulk enumeration of all stored items. The redundancy in retrieval tools also suggests an incomplete design.