VarynForge

Lint draft

lint_draft

Submit a draft for verification against its brief. Returns a pass/flag verdict with per-check detail. Pass moves the article to ready_to_publish; flag moves it to draft_ready for revision. channel (article | reels | youtube | x | linkedin) declares WHICH of the suggestion's per-channel briefs the draft is graded against AND the submission shape — always pass it for non-article content; when omitted, the channel is inferred from format. Submission shapes (get_lint_rubric returns the same spec + the numeric limits): article = markdown draft; x = thread text with one post per --- separated section, NO links in post bodies (put links in a reply); linkedin = post/caption text first, optional --- separated carousel slides after, NO links in the body (put links in the first comment); reels/youtube = the production SCRIPT — the process is brief -> script -> video, this gate validates the script, and the video is produced after it passes (published URL is recorded at publish time, not here). format labels the storage destination: prefer one of the project's destination type ids (see list_destinations) so receipts and drafts group per destination — re-submitting the same format replaces that destination's draft, a different format keeps both. The response reports the suggestion's post-lint status and a nextAction hint; thresholds is the article ratio block on the article channel and null otherwise (channel limits live in get_lint_rubric checkParams). waiveChecks marks check ids the OPERATOR deliberately deviates from (e.g. a brief section they dropped on purpose): waived checks still run and are recorded as waived in the receipt, but no longer fail the verdict — only pass ids the operator explicitly waived, never waive on your own initiative. Verdicts and drafts are stored per format and re-readable any time via get_draft_status (free — never re-lint to recover a lost verdict). Status transitions are forward-only: a flagged re-submit never demotes a suggestion already at ready_to_publish or published. Daily-capped (cap and remaining are in get_account_status limits); re-submitting an unchanged draft is served from cache.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`draft`	Yes
`format`	No
`channel`	No
`waiveChecks`	No
`suggestionId`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

The description richly discloses side effects beyond the sparse annotations: pass moves status, flag moves to draft_ready, re-submission replaces same-format drafts, status transitions are forward-only, waived checks still run, and unchanged drafts are cached. These are exactly the behavioral details an agent needs and cannot infer from annotations or schema.

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 description is long but information-dense and every clause adds operational value. It is front-loaded with the core purpose, though the dense single-block structure with multiple parentheticals could be easier to scan with bullets or section breaks.

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 tool with no output schema and high complexity, the description is complete: it explains return fields, thresholds behavior, channel-specific check limits location, storage semantics, quota handling, caching, and forward-only transitions. An agent can correctly select and invoke this tool without needing to open sibling tool schemas.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden, and it pays off: it explains channel enum semantics and submission shapes, format storage/replacement rules, waiveChecks operator intent, and draft content expectations per channel. Even suggestionId is clarified as referring to the suggestion whose brief is being graded.

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 action and resource: 'Submit a draft for verification against its brief' and states the pass/flag verdict outcome. It clearly distinguishes itself from sibling tools by framing linting as a draft gate tied to status transitions, not an idea/brief/research operation.

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?

It gives explicit usage rules: always pass `channel` for non-article content, use `format` for grouping, never re-lint to recover a lost verdict, and consult get_draft_status for stored results. It also directs users to get_lint_rubric for numeric limits and get_account_status for the daily cap, making alternatives and exclusions explicit.

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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