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Tulina

by ai.tulina.mcp
OverviewDiscussionsAdmin

frenchtech_membres

List community members (named people fiches).

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": "frenchtech_membres"
  }
}

Input Schema

NameRequiredDescriptionDefault
_orgNoOrg (id) de CET APPEL. `oto_list_orgs()`.
queryNo
_groupNoÉquipe (id) de CET APPEL, sous son org parente.
_run_idNoOBLIGATOIRE à chaque appel dès `run_start` ou `data_claim_next` : sans lui, l'écriture sur une ligne réservée est refusée. Hérité seulement si le serveur tient un run actif — n'y compte pas.
_projectNoProjet (id) de CET APPEL — jeton PRIMAIRE. `oto_project(op='list')`.
_instanceNoInstance de connecteur PRÉCISE (un credential exact). `oto_instance(op='list')`.
all_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the entire burden. "List" implies a non-mutating read, but nothing is said about pagination, result volume, whether all members are returned or a page, required org/project scoping, or what the response contains.

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?

One tight sentence with the resource front-loaded and no filler. It is efficiently written; the problem is under-specification, which is penalized elsewhere rather than for verbosity here.

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?

A 7-parameter tool with no annotations and no output schema needs the description to explain scoping (`_org`/`_project`/`_instance`), run-id requirements, and return shape. The description covers none of this and leaves the agent guessing at call semantics.

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?

Seven parameters with 71% schema coverage leaves `query` and `all_results` undocumented in both schema and description. The description adds no meaning at all to the input surface — notably it never explains what `query` filters on for a "list" tool or what `all_results` changes.

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

Purpose3/5

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

"List community members" states a verb and a resource, and the parenthetical "named people fiches" hints that records are person-level entries. But it never contrasts with the sibling frenchtech_search_annuaire, so an agent cannot tell from the description why it would pick listing over searching.

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?

There is no when-to-use guidance, no exclusion, and no mention of the obvious alternative (frenchtech_search_annuaire). The agent must infer that this is the unfiltered enumeration path rather than a targeted lookup.

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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