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cognitive_refine_lattice_from_feedback

Autonomously evolve higher-order invariants, tighten bounds, and discover cliques from execution feedback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lattice_idNo
default_rateNo
lattice_dataNo
feedback_tracesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It focuses on the action (evolve/tighten/discover) but omits what happens to existing lattice data, whether it mutates state, if it requires specific inputs, or if it's reversible. 'Autonomously' hints at side effects but is vague; no mention of mutation or side effects.

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?

Single sentence with key actions front-loaded; no redundancy. However, it uses specialized terms like 'higher-order invariants' and 'cliques' that may need elaboration for clarity, but the sentence itself is concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description is incomplete for a tool that likely mutates a lattice (evolve, tighten). It doesn't state what outputs to expect, what input is required (though all params are optional), or how to handle failures. Given the complexity and zero schema coverage, more detail is needed.

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

Parameters2/5

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

Schema coverage is 0%—no descriptions in the schema. The description mentions 'execution feedback' but doesn't explain that feedback_traces should contain execution logs, nor what lattice_data should be. With 4 optional parameters, the description does not compensate for the lack of schema documentation, leaving parameter semantics unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description has a specific verb 'evolve' with resource 'higher-order invariants, tighten bounds, discover cliques' from 'execution feedback', clearly distinguishing it from compile/verify lattice siblings. However, 'autonomously' may imply it does more than a single invocation, which could confuse an agent about side effects.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives like cognitive_compile_invariant_lattice or cognitive_verify_lattice_transition. The description implies it consumes feedback_traces but doesn't state prerequisites, nor when not to use it, leaving the agent to infer.

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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