Will It Stick

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.

Hand it a draft and its goal; get back the version that sticks. The tool scans the draft for its real point (every part of it, human stakes first), then writes three transformations: a CONCRETE COMPARISON (the key fact restated as something the reader can see, the popcorn move), a CORE COMPRESSION (the one line the reader must repeat, like 'School is cancelled'), and a SCENE (one concrete moment built only from what the draft holds). A code fact gate drops any transformation whose numbers are not stated in the draft or a plain derivation of stated numbers; nothing is ever invented. Then cold readers pick the winner by a gist test: each candidate is read cold, the reader's one-line gist is scored against the point and the key fact, and the best-carrying version wins. The author's ORIGINAL competes as a candidate and can win outright: status 'already_sticks' means the words already stick and the original is the version to send. If the scan finds the core is unreachable without inventing (the draft needs a name, a scene, or an identity line only the author holds), the first result has status 'questions_first' with up to three short questions; pass the author's answers back as answers on a second call, or set skip_questions true to transform the words as they stand. The result returns the winning version with its kind label, the original alongside, the losing transformations as alternates, and what a cold reader carried away from the winner. Takes about half a minute: cold readers are not instant. Use check_if_it_sticks instead when the human wants the diagnosis and scores first. Your words are not recorded or kept; the server keeps only daily counts of how many runs happened (integers, no text). The 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.