clusters.listList all principle clusters with their stable slugs and linked principle titles. Use this to discover which clusters exist before drilling in with clusters.get or filtering principles.list by cluster. Prefer clusters.get when you already know the cluster slug and need full detail.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, destructiveHint. Description adds no further behavioral traits beyond reinforcing non-destructive read nature but mentions output fields. No contradiction.
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?
Three sentences with no wasted words. Purpose, usage guidance, and alternative recommendation are efficiently presented.
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 zero parameters and low complexity, description is fully complete: covers purpose, usage context, and output fields. Output schema exists to handle return structure.
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?
No parameters; baseline is 4. Description does not need to add parameter info but indirectly describes output fields which is helpful.
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?
Clear verb 'list' and resource 'principle clusters' with explicit output details (stable slugs, linked principle titles). Distinguishes from siblings clusters.get and principles.list.
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?
Explicitly states when to use (discover clusters before drilling in) and when to prefer alternative (clusters.get for full detail). Also mentions filtering with principles.list.
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.
Each tool targets a clearly distinct purpose. For example, architect.validate vs architect.validate_consensus differ in single-shot vs consensus; handoffs.agency, handoffs.operator, and handoffs.partnership are separated by engagement type. No significant overlap.
Tools follow a consistent dot-notation grouping (architect.*, clusters.*, examples.*, guides.*, handoffs.*, me.*, principles.*, signals.*, team.*) with predictable verbs (validate, list, get, search, add, etc.). Minor deviation: some underscore within names (e.g., me.add_evidence) but overall pattern holds.
24 tools is on the higher side but justified given the broad domain spanning validation, certification, learning, handoffs, and feedback. Each tool has a clear role, and the count reflects the platform's comprehensive scope without feeling bloated.
The tool surface covers the full workflow (validate → consensus → certify), discovery (principles, clusters, examples, guides), personal progress (learning path, coaching, evidence), handoffs (support, partnership, agency), feedback, and team summaries. No obvious gaps for the stated purpose.