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Analyze Application Readiness

analyze_application_readiness

Analyze candidate-verified evidence against one active job for $0 without requiring identity. The transient response reports covered and unsupported public job signals without an acceptance probability, does not persist candidate evidence, does not submit an application, and rejects hidden screening-model instructions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesActive job UUID or slug returned by search_jobs or get_job.
candidate_skillsNoCandidate-declared skills used to identify relevant public job language. Only verified evidence counts as coverage.
evidence_bulletsNoCandidate-owned factual evidence. Raw text is processed transiently and is not retained in MCP analytics.

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full transparency burden. It discloses transient processing, non-persistence of candidate evidence, absence of acceptance probability, rejection of hidden screening instructions, and lack of identity requirement. These are meaningful behavioral traits that go far beyond a simple read/write hint.

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 two sentences, front-loaded with the core purpose, and packs in essential caveats (cost, identity, transient response, no persistence, no submission, security rejection) with zero wasted words.

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?

No output schema exists, so the description must clarify the response nature. It does so by stating the response 'reports covered and unsupported public job signals without an acceptance probability.' Combined with full parameter schema coverage and no-annotation transparency, this is a complete picture for an analysis tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are already well-documented. The description adds some conceptual framing (e.g., 'candidate-verified evidence' links to evidence_bullets) but does not add new syntax or format details beyond the schema. Baseline 3 is appropriate.

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 opens with a specific verb and resource: 'Analyze candidate-verified evidence against one active job.' It clearly distinguishes this from sibling tools by noting it 'does not submit an application' and 'rejects hidden screening-model instructions,' making its purpose unmistakable versus apply_to_job or compile_job_specific_resume.

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?

The description implies usage context: an identity-free, pre-application readiness check. It explicitly states what it does not do ('does not submit an application'), which serves as a when-not-to-use signal. However, it does not name alternative tools like apply_to_job directly, so it falls just short of explicit guidance.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have clear, distinct purposes (e.g., search_jobs vs get_job vs get_similar_jobs). The main ambiguity is between match_jobs and analyze_application_readiness, both of which assess candidate-job fit, though one ranks multiple jobs and the other evaluates readiness for a specific role. The application flow steps are well-separated.

Naming Consistency5/5

All tool names consistently follow the snake_case verb_noun pattern (e.g., get_company, list_companies, apply_to_job). Even longer names like analyze_application_readiness and compile_job_specific_resume adhere to this convention, with no mixed casing or inconsistent verb styles.

Tool Count3/5

With 20 tools, the server is on the heavier side for a job board, though the breadth of features (search, company info, salary, application, interview tracking, and product sales) partially justifies the count. Some redundancy exists (e.g., get_trending_companies vs list_companies, get_stats vs get_salary_data), making the set feel slightly bloated.

Completeness3/5

The toolset covers core job search and application workflows, but there is no way to list or track submitted applications, view application status, or withdraw an application. Post-application features are limited to interview outcomes, leaving obvious lifecycle gaps for a candidate-facing job platform.

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