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christophejlegros-lgtm

ASTRA — Unified Research Lab + MCP Server

tcai_convergence

Check or update convergence thresholds for the recursive double-loop halting criterion. Halting requires free energy convergence, high task quality, and low epistemic value sustained over patience cycles.

Instructions

Inspect or configure the recursive double-loop halting criterion (v2.8). With no arguments, returns the current satisfaction state and active thresholds. With arguments, updates them. The loop halts only when variational free energy has settled (|ΔF| ≤ epsFreeEnergy) AND realized task quality is high (≥ minTaskQuality) AND epistemic value is low, sustained over patience cycles — stationarity alone is insufficient (Legros 2026 §2.2/§4.3).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patienceNoConsecutive satisfied cycles required to halt (default 3)
maxEpistemicNoHalt threshold: expected info gain ≤ (default 0.1)
epsFreeEnergyNoHalt threshold: absolute |ΔF| ≤ (nats, default 0.02)
relFreeEnergyNoHalt threshold: |ΔF| ≤ rel·F, scale-free (default 0.03)
minTaskQualityNoHalt threshold: realized task quality ≥ (default 0.6)
Behavior5/5

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

No annotations provided, so description carries full burden. It explains the halting condition in detail, including the three criteria (free energy, task quality, epistemic value) and the patience cycles requirement. References external source for further details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences: purpose, read vs write mode, and halting condition. Efficient and well-structured, no wasted words.

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?

Given no output schema, description indicates return of satisfaction state and active thresholds. Parameters are all optional and described. Complete for a read/write configuration tool.

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 covers all 5 parameters with descriptions. The tool description adds collective context by explaining how parameters relate to the halting condition, but does not individually elaborate beyond the schema.

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?

The description clearly states the tool inspects or configures the halting criterion, specifying that no arguments returns state and arguments update thresholds. This distinguishes it from sibling tools like tcai_cycle or tcai_workspace_state.

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?

Explicitly describes two usage modes: read (no arguments) and write (with arguments). Provides clear condition for each. However, lacks explicit guidance on when to use this over sibling tools like tcai_cycle or tcai_metrics.

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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