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Analyze a job offer

analyze_offer

Analyse a job offer the user received and draft the negotiation scripts. Takes the offer text exactly as they got it — the recruiter's email, message or their own notes; the numbers are extracted from that wording, so a retold or summarised version loses them. Runs asynchronously: this returns an offer_id immediately, and get_offer(offer_id) shows the verdict, the market comparison and the counter-offer email once done. vacancy_id links the offer to a tracked vacancy. The market is read for where the user lives and how they are hired: pass candidate_country, employer_country and employment_type when the user said them; a left-out country is taken from their profile. Counts as one offer analysis against the user's plan — the free plan allows one a month. Returns 'limit_exceeded' when the quota is spent, 'no_resume' when the user has no resume to compare against, 'draft_limit_reached' when too many offers are waiting to be finished, 'not_found' for a foreign vacancy_id, and 'invalid_payload' for empty or oversized text.

Input Schema

NameRequiredDescriptionDefault
inputYes

Output Schema

NameRequiredDescriptionDefault
statusNoAlways 'processing' — the analysis runs asynchronously.processing
task_idYesBackground task id (informational; get_offer shows progress).
offer_idYesId of the created offer; pass to get_offer once ready.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare readOnly=false, destructive=false, idempotent=false; the description goes well beyond that with async semantics, the offer_id/get_offer handoff, per-plan quota accounting, the profile fallback for missing country, and five named error outcomes. This is exactly the behavioral context annotations cannot carry.

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?

Front-loads purpose, then the verbatim-input constraint, then async behavior and the get_offer follow-up, then parameters, then quota and error codes. It is dense but every sentence carries new information; nothing is padding.

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?

For an async, quota-metered write tool with a referenced schema and an output schema, the description covers invocation, retrieval of results, fallback behavior and failure modes. An agent has everything needed to call it and interpret the response.

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?

The nested schema already describes all five fields well, but the description still adds meaning: vacancy_id links the offer to the tracker, countries default to the profile when omitted, and source_text loses extracted numbers if paraphrased. The only gap is that it doesn't surface the employment_type enum values, which the schema does.

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+resource ('Analyse a job offer ... draft the negotiation scripts') and immediately distinguishes it from the vacancy/radar siblings by scoping to a received offer. An agent can tell this apart from analyze_vacancy and analyze_tracked_vacancy without opening a schema.

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?

Clearly says the source text must be verbatim wording from the recruiter and that summarised text loses the numbers, and it routes the agent to get_offer(offer_id) for the result. It also says when to pass optional fields ('when the user said them'). It lacks an explicit 'use X instead' for the vacancy-analysis siblings, so it stops short of a 5.

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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