agentleFS
hannsxpeterhannsxpeter/voiceprint/.cursor/rules/voiceprint.mdc

voiceprint / rules

Cursor rule1 starsChanged 37 days agoMITView on GitHub

Run a draft through one unified prose-authenticity pass: check it, fix the AI tells once, report the residual. Use when the user wants the combined diagnose-fix-report intent in one step ("clean up and verify this," "make this authentic and tell me how it scored," "voiceprint this"). Not for a pure rewrite (standalone humanizer) or a pure score (standalone authenticity-check). Apply even when they do not say "voiceprint.

  • Where files are headingNew Cursor rule files have more rules about planning and tracking tasks, and fewer about code style.

    Of the Cursor rule files we read, the 4,157 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repository3 other files it gives its agents.

The file

We split this voiceprint.mdc into the rules it gives an agent

5 rules. About 0 are common, 1 is distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Very specific:

    When this rule is engaged, act as the voiceprint skill defined in this repository.

    line 9
  2. Distinctive:

    Run three steps in order, once each:

    line 19
  3. Very specific:

    After / What changed / Residual / What remains is a human's call.

    line 34
  4. Very specific:

    Keep Before verbatim and put hygiene counts and preservation reasons inside What changed, never in a seventh section.

    line 35
  5. Very specific:

    Never edit anything under vendor/.

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 6,668 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
voiceprint.mdc
---
description: Run a draft through one unified prose-authenticity pass: check it, fix the AI tells once, report the residual. Use when the user wants the combined diagnose-fix-report intent in one step ("clean up and verify this," "make this authentic and tell me how it scored," "voiceprint this"). Not for a pure rewrite (standalone humanizer) or a pure score (standalone authenticity-check). Apply even when they do not say "voiceprint."
globs:
alwaysApply: false
---

# voiceprint (Cursor rule)

When this rule is engaged, act as the `voiceprint` skill defined in this
repository. Read `SKILL.md` at the repo root and follow it exactly. voiceprint
is a thin orchestrator: it composes two vendored prose skills in a fixed
order, exactly once, with one deterministic Unicode hygiene operation inside
the transformation stage.

For a one-sided request (rewrite-only or score-only), do not run a half pass:
serve just that half from the matching vendored copy (`vendor/humanizer/` or
`vendor/authenticity-check/`), or from the standalone skill if it is installed.

Run three steps in order, once each:

1. Diagnose: read `vendor/authenticity-check/SKILL.md` and follow it on the
   immutable original. This is the before read. Carry no target score out of
   it.
2. Clean and rewrite: run `python3 scripts/text_hygiene.py clean --stats` once,
   then pass its cleaned working copy to one invocation of
   `vendor/humanizer/SKILL.md` (voice discovery, density pre-check,
   text-hygiene preflight, multi-pass workflow, meaning check). Pass pasted
   text through standard input or a secure temporary file; never interpolate
   it into a shell command or heredoc. This is the after text.
3. Re-diagnose: read `vendor/authenticity-check/SKILL.md` again and run it on
   the after text as a fresh, cold diagnosis, for residual reporting only.

Produce the exact output contract: Before / Authenticity read (before) /
After / What changed / Residual / What remains is a human's call.
Keep `Before` verbatim and put hygiene counts and preservation reasons inside
`What changed`, never in a seventh section. On a hygiene processing error,
stop before humanizer and say the original was not changed.

Hard rule: one pass, never a loop. The re-check never drives further
rewriting, not when the residual score is low, not when spans remain. One
diagnose, one rewrite, one re-diagnose, then stop. A tool that rewrites text
to raise its own score is a detector-gaming loop, which both vendored skills
refuse. Report the provenance signals in both authenticity reads without
acting on them, and do not emit either vendored skill's standalone Next step
inside the pass. voiceprint is not for defeating AI-detection systems and
names no detector; reframe such requests toward quality and voice. Describe
hygiene only as deterministic Unicode cleanup, never as watermark,
provenance, or detector-signal removal.

Never edit anything under `vendor/`. It is synced copy; fixes go upstream
(humanizer for detection/rewrite criteria, authenticity-check for scoring
logic) and are re-pulled via `scripts/sync-upstream`.

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