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Will It Stick

Check if it sticks

check_if_it_sticks
Read-only

Use this when someone asks whether words they are about to send will land: 'Will this email land well?', 'How does this come across?', 'Could this be misunderstood?', 'Does this sound too harsh?', 'What might my manager misunderstand?' Three cold readers (a distracted stranger, a skeptic, and the target reader), each reading cold and never seeing the others, test how the message is actually received against the sender's stated goal. QUESTIONS FIRST: when the words leave gaps only the author can fill (the readers cannot find the point, the proof, or the specifics), the first result has status 'questions_first' and carries up to three short questions built from the readers' own complaints about this text, plus what the readers heard and where they split. Ask the author those questions, then call again with the same text and motivation plus answers to get the sharper, enriched verdict; if the author would rather not answer, call again with skip_questions true to get the verdict on the words as they stand. A verdict returns four plain grades out of 5, graded directly by the same readers in the same cold read (Easy to read, Holds your attention, The point lands, You'd pass it on; medians across the three readers), for conversation moments (a what's new update, a hard text) a walk_away pair: the thought the author wants the reader to leave with, from the goal, against the thought the readers may actually leave with, from what they heard, the core the readers heard (or the plain split when they heard different points), the readers' own notes including where they split, six SUCCESs medians with the spread between readers and a one-line reason each (the diagnostic layer underneath the plain grades), starter forms only (a proverb line, a curiosity-gap opener, a 3-4 sentence mini-story, concrete swaps for abstract phrases), the one prioritized fix for the element that most blocks the stated goal, and after_text: the draft copied exactly with only that one fix applied by a dedicated guarded step, when the bound passes (null when the bound discards it, with after_reason saying why; changed_lines counts the lines that differ). The tool never rewrites the draft in full; for the finished version itself, call make_it_stick, which returns the transformation cold readers carried away best (the same readers feed it). Do not use this for shortening, grammar fixes, translation, or generic 'make this clearer' rewriting; the host does those itself. Use it only to test how a finished draft will be received. Your words are not recorded or kept; the server keeps only a daily count of how many checks ran (integers, no text). The three readers run on Cloudflare Workers AI (Meta Llama 3.3 70B); under Cloudflare's published Workers AI terms, your text is not retained once it is no longer needed to answer, and it is never used to train AI models. Show the human the questions, scores, starters, and after_text as returned; the human decides what to send, and the tool sends nothing.

Input Schema

NameRequiredDescriptionDefault
textYesThe exact words to check: a message, note, toast, post, or pitch. A few sentences up to about 900 words.
momentNoOptional moment name, e.g. 'what's new', 'recommend something', 'a story I tell', 'say thanks', 'ask or invite', 'a hard text'. Helps the target reader sit in the right seat.
answersNoAnswers to a previous questions_first result, in the author's own words. Pass the same text and motivation, plus these, to get the enriched verdict.
motivationYesOne line: what should these words do? Who should do, feel, or remember what? Example: 'Get a friend to actually try the book I loved.'
skip_questionsNoSet true when the author declined the follow-up questions: returns the verdict on the words as they stand.

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?

The description goes well beyond the read-only annotation: it explains the three cold readers, the questions_first flow, verdict components, after_text guarding, and the bound/null behavior. It also discloses that text is not retained and that only an integer daily count is kept, which is valuable behavioral context.

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 trigger and main workflow are front-loaded, and most sentences carry useful information for a complex tool with no output schema. However, it is a very dense single paragraph with an extensive output inventory, which makes it harder to parse than necessary.

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?

There is no output schema, so the description must explain return behavior; it does so in detail, including questions_first, four grades, SUCCESs medians, walk_away, starters, prioritized fix, after_text, and null bounds. It also covers privacy, sibling routing, and limitations, making it complete for this 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 basic parameter meanings are already documented. The description adds workflow semantics that the schema does not fully convey: pass the same text and motivation with answers to enrich the verdict, or use skip_questions true when the author declines.

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 states a specific verb and resource: testing how a finished draft will be received by cold readers against the sender's goal. It explicitly distinguishes itself from the sibling make_it_stick and from host-side editing tasks such as shortening or grammar fixes.

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 concrete trigger phrases such as 'Will this email land well?' and explicit exclusions: do not use for shortening, grammar, translation, or generic rewriting. It also names make_it_stick as the alternative for producing a finished rewrite.

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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