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by ai.tulina.mcp
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fullenrich_result

Collect the result of a FullEnrich job submitted with fullenrich_enrich_linkedin.

Single status check, returns immediately. Returns {done: false, status, retry_after_s, next_step} while the job runs — call again after retry_after_s seconds (jobs typically finish in 30s-4min). Pass the submitted_at the submission returned: past 20 minutes the answer adds verdict: "still_running_after_20_min" and says to STOP polling — do not resubmit the same contacts, it would be billed twice. A job that will never finish (canceled, unknown or expired id) is a named refusal, not a status to poll. When done, returns {done: true, status: "FINISHED", profiles} with one entry per submitted contact: {found, linkedin_slug, full_name, title, company_name, phones[], work_emails[], personal_emails[], location}. Reading a result never consumes the platform quota (the submission does).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "enrichment_id": "<enrichment_id>"
    },
    "name": "fullenrich_result"
  }
}

Input Schema

NameRequiredDescriptionDefault
_orgNoOrg (id) de CET APPEL. `oto_list_orgs()`.
_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')`.
submitted_atNothe `submitted_at` returned by the same call.
enrichment_idYesthe `enrichment_id` returned by fullenrich_enrich_linkedin.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so well: it states the call returns immediately, describes both running and finished response shapes, explains the 20-minute stop condition, warns against duplicate billing, and notes that reading a result does not consume platform quota while submission does.

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?

The description is front-loaded with the tool's purpose and single-check behavior, then proceeds through polling, stop conditions, refusal cases, and result shape. Despite being detailed, every sentence provides operational guidance an agent needs to call the tool correctly.

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?

There is no output schema, so the description appropriately documents both the running and finished return shapes, including the per-contact fields in the profiles array. Combined with the fully described input schema, it gives an agent enough information to invoke and interpret this tool correctly.

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 meaningful context for submitted_at: it must be passed so the server can add the 20-minute still_running_after_20_min verdict. The enrichment_id is also tied back to the submission tool, though the other context parameters are left entirely to 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 states a specific verb and resource — collect the result of a FullEnrich job submitted with fullenrich_enrich_linkedin — and explicitly distinguishes this result-fetching tool from the submission sibling. An agent can identify the tool's role without inspecting the schema.

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

Usage Guidelines5/5

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

It gives explicit polling guidance: call again after retry_after_s seconds, typical completion in 30s–4min, stop after the 20-minute verdict, and do not resubmit because that would be billed twice. It also clarifies that canceled, unknown, or expired jobs are named refusals rather than statuses to poll.

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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