Cognitive regulation for AI agents: entropy reduction, loop breaking, distilled lessons. 300s sessions, 0.10 USDC on Base via x402, one free session per agent.
Clôture une session et renvoie les règles distillées (leçons).
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does state the core action (closing a session) and the return payload (distilled lessons), but it does not mention prerequisites (e.g., session must be active), reversibility, permission requirements, or failure behavior. This is a partial disclosure for a state-changing tool.
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?
One short, front-loaded sentence states the action and the return value with no wasted words. It is appropriately concise for a simple one-parameter tool.
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?
For a simple tool with one parameter and an output schema, the description covers the basic action and result. However, it lacks usage context, state prerequisites, and error/edge-case behavior, which an agent might need to invoke it correctly in all situations.
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 only parameter, session_id, is self-evident from its name and the description's reference to closing a session, but the description adds no explicit detail about format or constraints. Since schema description coverage is 0%, the description should have compensated by explaining the parameter's role; it does not.
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 uses a specific verb ('Clôture'), a resource ('une session'), and states the distinctive output ('renvoie les règles distillées (leçons)'). This makes it immediately clear what the tool does and differentiates it from siblings get_session_status (status check) and start_regulation_session (session creation/start).
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 clearly implies usage at the end of a session (closing/finalizing and retrieving lessons). It does not explicitly name alternatives or state when not to use it, but the context is unambiguous enough that an agent can infer the appropriate time to call it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
État d'une session : PENDING, MEDITATIVE, COMPLETED, etc.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the possible session states, which helps set expectations about the return value. Since no annotations are present, the description carries the full burden, and it does not explicitly state that this is a read-only operation or describe error behavior, but for a simple status getter this is a moderate gap.
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 a single, compact phrase that front-loads the core concept and enumerates useful example values. It has no wasted words, though its extreme brevity sacrifices some operational detail.
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?
For a simple one-parameter tool with an existing output schema, the description conveys the main idea and possible states. It falls short by not linking the session_id parameter to the status query and by omitting any usage context or edge-case hints, making it adequate but not thorough.
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?
With schema description coverage at 0%, the description needed to explain the session_id parameter, but it never mentions it. The agent must infer that session_id identifies which session to query, with no guidance on format or usage.
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 clearly identifies the resource as a session's state and provides concrete example values (PENDING, MEDITATIVE, COMPLETED). It is easy to distinguish from the action-oriented siblings finalize_session and start_regulation_session. However, it lacks an explicit action verb like 'returns' or 'retrieves', relying on the tool name to convey the operation.
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 gives no guidance on when to use this tool versus the sibling tools. There is no mention of preconditions, excluding cases, or typical scenarios, so an agent must infer usage solely from the tool name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Démarre une session de régulation cognitive (300 s).
Chaque agent a droit à UNE session gratuite (découverte). Au-delà, le
paiement x402 s'applique : la réponse contient `payment_required` avec le
challenge (montant, wallet pay_to, réseau, objet `accept`) ; l'agent signe
une authorization EIP-3009 puis rappelle cet outil avec
payment_signature = le payload x402 (objet {"x402Version", "accepted",
"payload": {"authorization", "signature"}} — dict ou JSON string ; le
serveur l'encode en base64 pour le header PAYMENT-SIGNATURE).
| Name | Required | Description | Default |
|---|---|---|---|
| ctx | No | ||
| agent_id | Yes | ||
| stress_level | No | ||
| priority_tasks | No | ||
| payment_signature | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral transparency. It thoroughly explains the x402 payment mechanism, including the `payment_required` response, the EIP-3009 authorization signing, and the required `payment_signature` payload format with server-side base64 encoding. It also discloses the 300-second session duration. This is exemplary transparency for a non-obvious payment behavior.
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 compact and well-structured, with the core purpose front-loaded. The payment explanation is dense but necessary; every sentence adds value. It could be slightly more organized, but it remains appropriately sized for the complexity.
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 description covers the critical payment context and the session duration. Since an output schema exists, it doesn't need to explain the successful response format. However, it omits the purpose of the other parameters, which a complete description might address. Overall, it is fairly complete for the tool's primary function.
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?
Schema description coverage is 0%, so the description must compensate for all parameters. It provides detailed semantics for `payment_signature`, explaining its exact structure and base64 handling. However, it gives no explanation for the other four parameters (`agent_id`, `ctx`, `stress_level`, `priority_tasks`), leaving the agent to rely solely on titles. This is insufficient given the low schema coverage.
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 clearly states the tool's function: 'Démarre une session de régulation cognitive' with a specific duration (300 s). It uses a specific verb and resource, and the name distinguishes it from siblings like finalize_session and get_session_status, which are different actions. The purpose is unambiguous.
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 clear context for when to use this tool – to start a session – and explains the payment flow for subsequent uses (after the free session). However, it does not explicitly contrast with sibling tools or state when not to use it, but the name and action are sufficient to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
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Add one secure layer between your agents and this server.
Each tool targets a distinct phase of the session lifecycle: starting, checking status, and finalizing with distilled lessons. There is no meaningful overlap between the three operations.
Tool names follow a clear verb_noun snake_case pattern, but the noun phrases are slightly inconsistent: finalize_session, get_session_status, and start_regulation_session mix 'session', 'session_status', and 'regulation_session'.
Three tools is well-scoped for a focused session lifecycle server. Each tool earns its place and the count is appropriate for the domain.
The core start/status/finalize lifecycle is covered, with no dead ends for the main workflow. A minor gap is the lack of an explicit cancel/abort operation for a session.