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sbanthia92

Second Read

review_document

Review a document draft with specialist agents that fact-check claims, build the strongest counter-case, check structure, copy edit, and flag unoriginal text, returning a sourced markdown report.

Instructions

Review a document draft with a desk of specialist agents: a fact-checker that cites sources, a devil's advocate that builds the strongest counter-case, a structure reviewer, a copy editor and an originality check. Returns a markdown report (must fix, counter-case, should fix, polish, originality notes, claim ledger). Pass exactly one of content (the text or markdown) or url (a public page). Reviews take a few minutes.

Input Schema

NameRequiredDescriptionDefault
urlNoA public http(s) page to fetch and review, instead of `content`.
focusNoOptional steer, e.g. "check the financial figures".
contentNoThe document text or markdown. Give this or `url`, not both.
profileNo`auto` (detect), `opinion` (essays, op-eds, posts) or `design_doc` (technical designs and proposals).auto

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it names the multi-agent review mechanism, lists the report sections returned, and warns that reviews take minutes. It does not clarify whether the call blocks for that duration or returns a job handle, which is the one behavioral gap left.

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?

The purpose and the exactly-one-input rule are front-loaded, and every sentence carries information. The roster of specialist agents is slightly verbose but it sets expectations for the output, so it earns its place.

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?

With no output schema, the description must explain the return value, and it does so explicitly by enumerating the markdown report sections. Input rules, latency and output format are all covered for a four-parameter tool.

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; the description earns above that by stating the mutual-exclusivity rule between `content` and `url`. The report-section list also implicitly maps to the `focus` and `profile` steers, though it doesn't spell out how `profile` changes reviewer behaviour.

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 and resource ("review a document draft") and enumerates the concrete review passes an agent can expect. No sibling tools exist, so there is no competing option an agent could confuse it with.

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?

Gives the explicit input constraint "Pass exactly one of `content` or `url`" and the latency expectation "Reviews take a few minutes", which is real guidance on when this call is appropriate. It stops short of true when/when-not framing (e.g. unsuitable document types) but there are no alternatives to route to.

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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