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Get write handoff

get_write_handoff
Read-only

One-call writer handoff: returns a compact writing payload for an article suggestion (brief essentials, keywords, acceptance criteria, lint instructions). Compact by design — FAQs cap at 6 and long sections degrade to fit a deep-link budget; the FULL brief is get_article_brief and the full check list is get_lint_rubric, so verify against those, not this. deepLinks (ChatGPT/Claude URLs embedding the payload) is null over MCP — it exists for web users without a connected agent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
suggestionIdYes

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses the compactness behavior: FAQs cap at 6 and long sections degrade to fit a deep-link budget. It also reveals that deepLinks is null over MCP, a runtime behavior an agent would not otherwise know. This adds valuable context not covered by the annotation.

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 concise and well structured: it opens with the core purpose, followed by limitations and alternatives, and ends with a specific field behavior. Every sentence adds value, and the most critical information (what it does) is front-loaded.

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?

Although there is no output schema, the description adequately explains what the payload contains, its limitations, and directs users to full sources. It covers the single parameter implicitly, notes the deepLinks behavior, and is complete for a one-call read tool. An agent has enough to invoke it correctly and interpret the response.

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?

The schema defines suggestionId with UUID format and pattern but no description. The tool description adds the context that it is 'for an article suggestion', clarifying the parameter's role. For a single well-named parameter, this is adequate but minimal—no additional details like how to obtain the ID or constraints beyond the format. Schema coverage is 0%, so the description does compensate partially but not thoroughly.

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 clearly states the tool 'returns a compact writing payload for an article suggestion', listing the specific contents (brief essentials, keywords, acceptance criteria, lint instructions). It also differentiates it from siblings by naming get_article_brief and get_lint_rubric as the full counterparts, so the purpose is unambiguous and distinct.

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?

Explicitly states when to use this tool vs. alternatives: 'the FULL brief is get_article_brief and the full check list is get_lint_rubric, so verify against those, not this.' This gives clear guidance that this is for quick access and that the full sources must be consulted for complete information. Also notes the deepLinks field becomes null over MCP, setting expectations for use.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but a few pairs could confuse an agent: add_article_suggestion vs create_article_suggestion_with_input, and get_article_brief vs download_brief_markdown vs get_write_handoff all deal with brief content. The detailed descriptions help disambiguate, but the overlap is real.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in lowercase snake_case (create_project, list_opportunities, generate_article_brief, lint_draft). There is no mixing of camelCase, acronyms, or vague verbs, making the naming predictable and readable.

Tool Count2/5

50 tools is excessive for an MCP server, even for a broad platform like content operations. While the scope is large, this many tools will overwhelm agents and increase latency and context cost. Most practical servers are well under 25.

Completeness4/5

The tool surface covers the full content lifecycle: project creation, research, opportunity clustering, content planning, briefs, drafting, linting, publishing, and reporting. Minor gaps exist (e.g., no delete_project, no remove_destination, no direct analytics beyond distributions), but they are workarounds or handled in the web UI.

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