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Ficiel MCP

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Lister les règles apprises

ficiel_list_learned_patterns
Read-onlyIdempotent

Liste les règles apprises par Kord (style, objections, ouvertures) avec leur état de validation. "proposed" = en attente de votre décision (voir ficiel_approve_learned_patterns, ficiel_dismiss_learned_patterns, ficiel_convert_learned_patterns), "approved" = adoptée, "dismissed" = écartée, "auto" = règle obligatoire de la plateforme (jamais proposée à la modification).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ficiel_list_learned_patterns"
  }
}

Input Schema

NameRequiredDescriptionDefault
active_onlyNotrue = seulement les règles actuellement actives.
review_stateNoFiltre par état. Sans filtre : toutes les règles.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: the four state values and the important constraint that 'auto' rules are platform-mandatory and never offered for modification, which an agent could not infer from annotations or schema alone.

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?

Two sentences, front-loaded with the core purpose, and the fairly long enum gloss is justified because those values drive agent decisions. Slightly dense but no sentence is filler.

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

Completeness4/5

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

For a read-only filtered list with no output schema, the description covers purpose, filter states, and follow-up actions. It stops short of indicating what a returned rule record contains (rule text, category, timestamps), a minor gap given there is no output schema to fall back on.

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 coverage is 100% so the baseline is 3, but the description adds meaning beyond the schema by explaining what each review_state enum value signifies in terms of workflow. It does not clarify the interaction between active_only and review_state, which keeps it from a 5.

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?

States a specific verb and resource ('Liste les règles apprises par Kord') and enumerates the rule categories (style, objections, ouvertures) plus the validation state carried in the result. An agent can distinguish this immediately from the sibling ficiel_approve/dismiss/convert_learned_patterns tools, which the description explicitly names.

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?

Explains that 'proposed' means awaiting the user's decision and points to the exact sibling tools to act on it (approve, dismiss, convert), which effectively routes read vs. write. It does not spell out a negative case (e.g., use this before deciding, not after), but the context is clear.

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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