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Headline Analyzer

headline_analyzer
Read-onlyIdempotent

Score and rank up to 20 headlines, best first. FREE.

Scores 0-100 on length, power/emotion words, numbers, structure, and clarity. Typical input {"headlines": ["7 Mistakes New Writers Make", "On Writing"]} returns {"ranked": [{"headline": ..., "score": 85, "notes": ["good length", "contains number"]}, ...]}.

Use when several title options need ranking. Not for email subject lines, which the outbound server's subject_line_scorer judges against deliverability signals, and not for body prose (analyze_writing). Errors: on invalid, missing, or malformed input this tool never raises a protocol error; it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

NameRequiredDescriptionDefault
headlinesYesList of candidate headlines as plain strings; only the first 20 are scored.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description goes further by documenting the error contract: malformed input never raises a protocol error and instead returns {"error": ...} with remediation, so retry after correction is safe. It also discloses the scoring dimensions and that the service is free, which an agent would otherwise have to discover by trial.

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?

Front-loaded with the core action and limit, followed by cost, scoring criteria, an example, routing guidance, and error semantics in that order. Slightly verbose in restating a return shape that the output schema already covers, but no sentence 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 a one-parameter read-only scorer with a declared output schema, the description covers purpose, limits, cost, error recovery, and sibling routing. An agent has everything needed to select and invoke it correctly on the first attempt.

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% and the single 'headlines' array parameter is already documented, so the baseline is 3. The description adds the 'up to 20' truncation behavior and a concrete example payload showing the plain-string array shape, which mildly exceeds 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?

States a specific verb pair (score and rank) on a specific resource (headlines), including the 20-item cap and the best-first ordering. It also explicitly names the sibling tools it is not (subject_line_scorer, analyze_writing), so an agent can disambiguate without opening schemas.

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?

Gives a positive trigger ('Use when several title options need ranking') and two explicit exclusions with the correct alternative for each: email subject lines go to the outbound server's subject_line_scorer, body prose goes to analyze_writing. Nothing is left to inference.

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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