rewrite first paragraph

Updates LLM_PROSE_TELLS.md with three new patterns (two-clause compound sentence, almost-hedge, unnecessary contrast), the lol section with conversation excerpts, fixes for instances of these patterns throughout, and a bracket escaping fix for prettier idempotency. Checklist is now 24 items.

Co-authored-by: user <user@Mac.lan guest wan>
Reviewed-on: #8
Co-authored-by: clawbot <clawbot@noreply.example.org>
Co-committed-by: clawbot <clawbot@noreply.example.org>

README.md

@@ -115,6 +115,31 @@ subdirectory. Each file contains one or more related prompts or policy
 documents. There is no build step or runtime component; the prompts are consumed
 by copying them into other projects or referencing them directly.
 
+## Template Repos
+
+These template repositories implement the policies defined in this repo and
+serve as starting points for new projects. They must be kept in sync when
+policies change.
+
+- **[template-app-go](https://git.eeqj.de/sneak/template-app-go)** — Go HTTP
+  server template (Uber fx, chi, SQLite, session auth, Prometheus metrics)
+- **[template-app-js](https://git.eeqj.de/sneak/template-app-js)** — JavaScript
+  SPA template (Vite, Tailwind CSS v4, nginx Docker deployment)
+- **[template-app-python](https://git.eeqj.de/sneak/template-app-python)** —
+  Python web application template (FastAPI, uvicorn, pytest, black, ruff)
+
+When updating policies in this repo, also update the template repos to match
+(Makefile targets, Dockerfile conventions, CI workflows, required files, etc.).
+
+## See Also
+
+- **[clawpub](https://git.eeqj.de/sneak/clawpub)** — Real-world examples,
+  rationale, and operational lessons from applying these policies with an
+  [OpenClaw](https://github.com/openclaw/openclaw) AI agent. Includes detailed
+  documentation on how the interlocking check system (CI → Docker → Makefile →
+  tests/lint/fmt) works in practice, why checklists complement prose policies,
+  and failure stories from production use.
+
 ## TODO
 
 - Add more prompt templates for common development tasks

prompts/CODE_STYLEGUIDE_GO.md

@@ -229,6 +229,29 @@ last_modified: 2026-02-22
 
 1.  Define your struct types near their constructors.
 
+1.  Do not create packages whose sole purpose is to hold type definitions.
+    Packages named `types`, `domain`, or `models` that contain only structs and
+    interfaces (with no behavior) are a code smell. Define types alongside the
+    code that uses them. Type-only packages force consuming packages into alias
+    imports and circular-dependency gymnastics, and indicate that the package
+    boundaries were drawn around nouns instead of responsibilities. If multiple
+    packages need the same type, put it in the package that owns the behavior,
+    or in a small, focused interface package — not in a grab-bag types package.
+
+1.  When defining custom string-based types (e.g. `type ImageID string`),
+    implement `fmt.Stringer`. Use `.String()` at SDK and library boundaries
+    instead of `string(v)`. This makes type conversions explicit, grep-able, and
+    consistent across the codebase. Example:
+
+    ```go
+    type ContainerID string
+
+    func (id ContainerID) String() string { return string(id) }
+
+    // At the Docker SDK boundary:
+    resp, err := c.docker.ContainerStart(ctx, id.String(), opts)
+    ```
+
 1.  Define your interface types near the functions that use them, or if you have
     multiple conformant types, put the interface(s) in their own file.
 

prompts/LLM_PROSE_TELLS.md

@@ -0,0 +1,514 @@
+# LLM Prose Tells
+
+Every pattern in this document shows up in human writing occasionally. They
+become diagnostic only through density. A person might use one or two across an
+entire essay, but LLM output packs fifteen into a single paragraph.
+
+---
+
+## Sentence Structure
+
+### The Em-Dash Pivot: "Not X—but Y"
+
+A negation followed by an em-dash and a reframe.
+
+> "It's not just a tool—it's a paradigm shift." "This isn't about
+> technology—it's about trust."
+
+The single most recognizable LLM construction. Models produce this at roughly 10
+to 50x the rate of human writers. Four of them in one essay and you know what
+you're reading.
+
+### Em-Dash Overuse Generally
+
+Even outside the "not X but Y" pivot, models use em-dashes at far higher rates
+than human writers. They substitute em-dashes for commas, semicolons,
+parentheses, colons, and periods, often multiple times per paragraph. A human
+writer might use one or two in an entire piece for a specific parenthetical
+effect. Models scatter them everywhere because the em-dash can stand in for any
+other punctuation mark, so they default to it. More than two or three per page
+is a meaningful signal on its own.
+
+### The Colon Elaboration
+
+A short declarative clause, then a colon, then a longer explanation.
+
+> "The answer is simple: we need to rethink our approach from the ground up."
+
+Models reach for this in every other paragraph. The construction is perfectly
+normal. The frequency gives it away.
+
+### The Triple Construction
+
+> "It's fast, it's scalable, and it's open source."
+
+Three parallel items in a list, usually escalating. Always exactly three (rarely
+two, never four) with strict grammatical parallelism that human writers rarely
+bother maintaining.
+
+### The Staccato Burst
+
+> "This matters. It always has. And it always will." "The data is clear. The
+> trend is undeniable. The conclusion is obvious."
+
+Runs of very short sentences at the same cadence. Human writers use a short
+sentence for emphasis occasionally, but stacking three or four of them in a row
+at matching length creates a mechanical regularity that reads as generated.
+
+### The Two-Clause Compound Sentence
+
+Possibly the most pervasive structural tell, and easy to miss because each
+individual instance looks like normal English. The model produces sentence after
+sentence where an independent clause is followed by a comma, a conjunction
+("and," "but," "which," "because"), and a second independent clause of similar
+length. Every sentence becomes two balanced halves joined in the middle.
+
+> "The construction itself is perfectly normal, which is why the frequency is
+> what gives it away." "They contain zero information, and the actual point
+> always comes in the paragraph that follows them." "The qualifier never changes
+> the argument that follows it, and its purpose is to perform nuance rather than
+> to express an actual reservation."
+
+Human prose has sentences with one clause, sentences with three, sentences that
+start with a subordinate clause before reaching the main one, sentences that
+embed their complexity in the middle. When every sentence on the page has that
+same two-part structure, the rhythm becomes monotonous in a way that's hard to
+pinpoint but easy to feel.
+
+### Uniform Sentences Per Paragraph
+
+Model-generated paragraphs contain between three and five sentences. This count
+holds steady across an entire piece. If the first paragraph has four sentences,
+every subsequent paragraph will too. Human writers are much more varied (a
+single sentence followed by one that runs eight or nine) because they follow the
+shape of an idea, not a template.
+
+### The Dramatic Fragment
+
+Sentence fragments used as standalone paragraphs for emphasis, like "Full stop."
+or "Let that sink in." on their own line. Using one in an entire essay is a
+reasonable stylistic choice, but models drop them in once per section or more,
+at which point it becomes a habit rather than a deliberate decision.
+
+### The Pivot Paragraph
+
+> "But here's where it gets interesting." "Which raises an uncomfortable truth."
+
+One-sentence paragraphs that exist only to transition between ideas. They
+contain zero information. The actual point is always in the next paragraph.
+Delete every one of these and the piece reads better.
+
+### The Parenthetical Qualifier
+
+> "This is, of course, a simplification." "There are, to be fair, exceptions."
+
+Parenthetical asides inserted to look thoughtful. The qualifier never changes
+the argument that follows it. Its purpose is to perform nuance, not to express a
+real reservation about what's being said.
+
+### The Unnecessary Contrast
+
+Models append a contrasting clause to statements that don't need one, tacking on
+"whereas," "as opposed to," "unlike," or "except that" to draw a comparison the
+reader could already infer.
+
+> "Models write one register above where a human would, whereas human writers
+> tend to match register to context."
+
+The first clause already makes the point. The contrasting clause restates it
+from the other direction. If you delete the "whereas" clause and the sentence
+still says everything it needs to, the contrast was filler.
+
+### Unnecessary Elaboration
+
+Models keep going after the sentence has already made its point, tacking on
+clarifying phrases, adverbial modifiers, or restatements that add nothing.
+
+> "A person might lean on one or two of these habits across an entire essay, but
+> LLM output will use fifteen of them per paragraph, consistently, throughout
+> the entire piece."
+
+This sentence could end at "paragraph." The words after it just repeat what "per
+paragraph" already means. Models do this because they're optimizing for clarity
+at the expense of concision, and because their training rewards thoroughness.
+The result is prose that feels padded. If you can cut the last third of a
+sentence without losing any meaning, the last third shouldn't be there.
+
+### The Question-Then-Answer
+
+> "So what does this mean for the average user? It means everything."
+
+A rhetorical question immediately followed by its own answer. Models do this two
+or three times per piece because it fakes forward momentum. A human writer might
+do it once.
+
+---
+
+## Word Choice
+
+### Overused Intensifiers
+
+The following words appear at dramatically elevated rates in model output:
+"crucial," "vital," "robust," "comprehensive," "fundamental," "arguably,"
+"straightforward," "noteworthy," "realm," "landscape," "leverage" (as a verb),
+"delve," "tapestry," "multifaceted," "nuanced" (which models apply to their own
+analysis with startling regularity), "pivotal," "unprecedented" (frequently
+applied to things with plenty of precedent), "navigate," "foster,"
+"underscores," "resonates," "embark," "streamline," and "spearhead." Three or
+more on the same page is a strong signal.
+
+### Elevated Register Drift
+
+Models write one register above where a human would. "Use" becomes "utilize."
+"Start" becomes "commence." "Help" becomes "facilitate." "Show" becomes
+"demonstrate." "Try" becomes "endeavor." "Change" becomes "transform." "Make"
+becomes "craft." The tendency holds regardless of topic or audience.
+
+### Filler Adverbs
+
+"Importantly," "essentially," "fundamentally," "ultimately," "inherently,"
+"particularly," "increasingly." Dropped in to signal that something matters,
+which is unnecessary when the writing itself already makes the importance clear.
+
+### The "Almost" Hedge
+
+Models rarely commit to an unqualified statement. Instead of saying a pattern
+"always" or "never" does something, they write "almost always," "almost never,"
+"almost certainly," "almost exclusively." The word "almost" shows up at
+extraordinary density in model-generated analytical prose. It's a micro-hedge,
+less obvious than the full hedge stack but just as diagnostic when it appears
+ten or fifteen times in a single document.
+
+### "In an era of..."
+
+> "In an era of rapid technological change..."
+
+A model habit as an essay opener. The model uses it to stall while it figures
+out what the actual argument is. Human writers don't begin a piece by zooming
+out to the civilizational scale before they've said anything specific.
+
+---
+
+## Rhetorical Patterns
+
+### The Balanced Take
+
+> "While X has its drawbacks, it also offers significant benefits."
+
+Every argument followed by a concession, every criticism softened. A direct
+artifact of RLHF training, which penalizes strong stances. Models reflexively
+both-sides everything even when a clear position would serve the reader better.
+
+### The Throat-Clearing Opener
+
+> "In today's rapidly evolving digital landscape, the question of data privacy
+> has never been more important."
+
+The first paragraph of most model-generated essays adds no information. Delete
+it and the piece improves immediately. The actual argument starts in paragraph
+two.
+
+### The False Conclusion
+
+> "At the end of the day, what matters most is..." "Moving forward, we must..."
+
+The high school "In conclusion,..." dressed up for a professional audience.
+Signals that the model is wrapping up without actually landing on anything.
+
+### The Sycophantic Frame
+
+> "Great question!" "That's a really insightful observation."
+
+No one who writes for a living opens by complimenting the assignment.
+
+### The Listicle Instinct
+
+Models default to numbered or bulleted lists even when prose would be more
+appropriate. The lists contain exactly 3, 5, 7, or 10 items (never 4, 6, or 9),
+use rigidly parallel grammar, and get introduced with a preamble like "Here are
+the key considerations:"
+
+### The Hedge Stack
+
+> "It's worth noting that, while this may not be universally applicable, in many
+> cases it can potentially offer significant benefits."
+
+Five hedges in one sentence ("worth noting," "while," "may not be," "in many
+cases," "can potentially"), communicating nothing. The model would rather be
+vague than risk being wrong about anything.
+
+### The Empathy Performance
+
+> "This can be a deeply challenging experience." "Your feelings are valid."
+
+Generic emotional language that could apply equally to a bad day at work or a
+natural disaster. That interchangeability is what makes it identifiable.
+
+---
+
+## Structural Tells
+
+### Symmetrical Section Length
+
+If the first section of a model-generated essay runs about 150 words, every
+subsequent section will fall between 130 and 170. Human writing is much more
+uneven, with 50 words in one section and 400 in the next.
+
+### The Five-Paragraph Prison
+
+Model essays follow a rigid introduction-body-conclusion arc even when nobody
+asked for one. The introduction previews the argument, the body presents 3 to 5
+points, and then the conclusion restates the thesis using slightly different
+words.
+
+### Connector Addiction
+
+Look at the first word of each paragraph in model output. You'll find an
+unbroken chain of transition words: "However," "Furthermore," "Moreover,"
+"Additionally," "That said," "To that end," "With that in mind," "Building on
+this." Human prose moves between ideas without announcing every transition.
+
+### Absence of Mess
+
+Model prose doesn't contradict itself mid-paragraph and then catch the
+contradiction. It doesn't go on a tangent and have to walk it back, use an
+obscure idiom without explaining it, make a joke that risks falling flat, leave
+a thought genuinely unfinished, or keep a sentence the writer liked the sound of
+even though it doesn't quite work.
+
+Human writing does all of those things regularly. That total absence of rough
+patches and false starts is one of the strongest signals that text was
+machine-generated.
+
+---
+
+## Framing Tells
+
+### "Broader Implications"
+
+> "This has implications far beyond just the tech industry."
+
+Zooming out to claim broader significance without substantiating it. The model
+has learned that essays are supposed to gesture at big ideas, so it gestures.
+Nothing concrete is behind the gesture.
+
+### "It's important to note that..."
+
+This phrase and its variants ("it's worth noting," "it bears mentioning," "it
+should be noted") appear at absurd rates in model output. They function as
+verbal tics before a qualification the model believes someone expects.
+
+### The Metaphor Crutch
+
+Models rely on a small, predictable set of metaphors ("double-edged sword," "tip
+of the iceberg," "north star," "building blocks," "elephant in the room,"
+"perfect storm," "game-changer") and reach for them with unusual regularity
+across every topic. The pool is noticeably smaller than what human writers draw
+from.
+
+---
+
+## How to Actually Spot It
+
+No single pattern on this list proves anything by itself. Humans use em-dashes.
+Humans write "crucial." Humans ask rhetorical questions.
+
+What gives it away is how many of these show up at once. Model output will hit
+10 to 20 of these patterns per page. Human writing might trigger 2 or 3,
+distributed unevenly, mixed with idiosyncratic constructions no model would
+produce. When every paragraph on the page reads like it came from the same
+careful, balanced, slightly formal, structurally predictable process, it was
+generated by one.
+
+---
+
+## Copyediting Checklist: Removing LLM Tells
+
+Follow this checklist when editing any document to remove machine-generated
+patterns. Go through the entire list for every piece. Do at least two full
+passes, because fixing one pattern often introduces another.
+
+### Pass 1: Word-Level Cleanup
+
+1. Search the document for every word in the overused intensifiers list
+   ("crucial," "vital," "robust," "comprehensive," "fundamental," "arguably,"
+   "straightforward," "noteworthy," "realm," "landscape," "leverage," "delve,"
+   "tapestry," "multifaceted," "nuanced," "pivotal," "unprecedented,"
+   "navigate," "foster," "underscores," "resonates," "embark," "streamline,"
+   "spearhead") and replace each one with a plainer word, or delete it if the
+   sentence works without it.
+
+2. Search for filler adverbs ("importantly," "essentially," "fundamentally,"
+   "ultimately," "inherently," "particularly," "increasingly") and delete every
+   instance where the sentence still makes sense without it. That will be most
+   of them.
+
+3. Look for elevated register drift ("utilize," "commence," "facilitate,"
+   "demonstrate," "endeavor," "transform," "craft" and similar) and replace with
+   the simpler word.
+
+4. Search for "it's important to note," "it's worth noting," "it bears
+   mentioning," and "it should be noted" and delete the phrase in every case.
+   The sentence that follows always stands on its own.
+
+5. Search for the stock metaphors ("double-edged sword," "tip of the iceberg,"
+   "north star," "building blocks," "elephant in the room," "perfect storm,"
+   "game-changer," "at the end of the day") and replace them with something
+   specific to the topic, or just state the point directly.
+
+6. Search for "almost" used as a hedge ("almost always," "almost never," "almost
+   certainly," "almost exclusively") and decide in each case whether to commit
+   to the unqualified claim or to drop the sentence entirely. If the claim needs
+   "almost" to be true, it might not be worth making.
+
+7. Search for em-dashes and replace each one with the punctuation mark that
+   would normally be used in that position (comma, semicolon, colon, period, or
+   parentheses). If you can't identify which one it should be, the sentence
+   needs to be restructured.
+
+### Pass 2: Sentence-Level Restructuring
+
+8. Find every em-dash pivot ("not X...but Y," "not just X...Y," "more than
+   X...Y") and rewrite it as two separate clauses or a single sentence that
+   makes the point without the negation-then-correction structure.
+
+9. Find every colon elaboration and check whether it's doing real work. If the
+   clause before the colon could be deleted without losing meaning, rewrite the
+   sentence to start with the substance that comes after the colon.
+
+10. Find every triple construction (three parallel items in a row) and either
+    reduce it to two, expand it to four or more, or break the parallelism so the
+    items don't share the same grammatical structure.
+
+11. Find every staccato burst (three or more short sentences in a row at similar
+    length) and combine at least two of them into a longer sentence, or vary
+    their lengths so they don't land at the same cadence.
+
+12. Find every unnecessary contrast ("whereas," "as opposed to," "unlike," "as
+    compared to," "except that") and check whether the contrasting clause adds
+    information not already obvious from the main clause. If the sentence says
+    the same thing twice from two directions, delete the contrast.
+
+13. Check for the two-clause compound sentence pattern. If most sentences in a
+    passage follow the "\[clause\], \[conjunction\] \[clause\]" structure,
+    rewrite some of them. Break a few into two sentences. Start some with a
+    subordinate clause. Embed a relative clause in the middle of one instead of
+    appending it at the end. The goal is variety in sentence shape, not just
+    sentence length.
+
+14. Find every rhetorical question that is immediately followed by its own
+    answer and rewrite the passage as a direct statement.
+
+15. Find every sentence fragment being used as its own paragraph and either
+    delete it or expand it into a complete sentence that adds actual
+    information.
+
+16. Check for unnecessary elaboration at the end of sentences. Read the last
+    clause or phrase of each sentence and ask whether the sentence would lose
+    any meaning without it. If not, cut it.
+
+17. Find every pivot paragraph ("But here's where it gets interesting." and
+    similar) and delete it. The paragraph after it always contains the actual
+    point.
+
+### Pass 3: Paragraph and Section-Level Review
+
+18. Check paragraph lengths across the piece and verify they actually vary. If
+    most paragraphs have between three and five sentences, rewrite some to be
+    one or two sentences and let others run to six or seven.
+
+19. Check section lengths for suspicious uniformity. If every section is roughly
+    the same word count, combine some shorter ones or split a longer one
+    unevenly.
+
+20. Check the first word of every paragraph for chains of connectors ("However,"
+    "Furthermore," "Moreover," "Additionally," "That said"). If more than two
+    transition words start consecutive paragraphs, rewrite those openings to
+    start with their subject.
+
+21. Check whether every argument is followed by a concession or qualifier. If
+    the piece both-sides every point, pick a side on at least some of them and
+    cut the hedging.
+
+22. Read the first paragraph and ask whether deleting it would improve the
+    piece. If it's scene-setting that previews the argument, delete it and start
+    with paragraph two.
+
+23. Read the last paragraph and check whether it restates the thesis or uses a
+    phrase like "at the end of the day" or "moving forward." If so, either
+    delete it or rewrite it to say something the piece hasn't said yet.
+
+### Pass 4: Overall Texture
+
+24. Read the piece aloud and listen for passages that sound too smooth, too
+    even, or too predictable. Human prose has rough patches. If there aren't
+    any, the piece still reads as machine output.
+
+25. Check that the piece contains at least a few constructions that feel
+    idiosyncratic: a sentence with unusual word order, a parenthetical that goes
+    on a bit long, an aside only loosely connected to the main point, a word
+    choice that's specific and unexpected. If every sentence is clean and
+    correct and unremarkable, it will still read as generated.
+
+26. Verify that you haven't introduced new patterns while fixing the original
+    ones. This happens constantly. Run the entire checklist again from the top
+    on the revised version.
+
+---
+
+## lol
+
+This document was written by an LLM (Claude) and then iteratively de-LLMed by
+that same LLM under instruction from a human, in a conversation that went
+roughly like this:
+
+> **human:** compile a list of patterns common to LLM-authored prose
+>
+> **model:** _(produces document full of LLM tells)_
+>
+> **human:** now reverse apply it to itself and copyedit the llm tells doc to
+> remove llm tells. now you're thinking with portals
+>
+> **model:** _(fixes some tells, introduces others)_
+>
+> **human:** you have a colon elaboration in the first paragraph. i want you to
+> AGGRESSIVELY de-LLM the llm tells doc.
+>
+> **model:** _(fixes more tells, still can't stop)_
+>
+> **human:** there's a big one we missed that's all over the llm tells doc, can
+> you spot it?
+>
+> **model:** I think it's the "almost" hedge.
+>
+> **human:** that too, but that isn't the one. what do these sentences all have
+> in common? _(pastes six sentences from the doc)_
+>
+> **model:** They're all exactly two independent clauses joined by a comma and a
+> conjunction. Every single one is "\[statement\], \[conjunction\] \[second
+> statement\]." The same sentence shape, over and over.
+>
+> **human:** the dramatic fragment paragraph has a tell in it
+>
+> **model:** "One of these in an entire essay is a stylistic choice. One per
+> section is a tic." Two-clause parallel structure with the same shape, and also
+> a staccato pair.
+>
+> **human:** add em dashes generally as a tell, and remove them all from the
+> tells doc
+>
+> **model:** _(rewrites entire document without em-dashes while describing
+> em-dash overuse)_
+>
+> **human:** now run the checklist methodically on each paragraph
+>
+> **model:** _(finds staccato burst in the section about triple constructions, a
+> triple in the section about absence of mess, two-clause compounds everywhere,
+> and "almost" hedges in its own prose about em-dash overuse)_
+
+The human compared this process to the deleted scene in Terminator 2 where John
+Connor switches the T-800's CPU to learning mode. The model compared it to a
+physician trying to heal itself. Both are accurate.
+
+This document has been through eight editing passes and it still has tells in
+it.

prompts/REPO_POLICIES.md

@@ -144,8 +144,14 @@ style conventions are in separate documents:
 - Use SemVer.
 
 - Database migrations live in `internal/db/migrations/` and must be embedded in
-  the binary. Pre-1.0.0: modify existing migrations (no installed base assumed).
-  Post-1.0.0: add new migration files.
+  the binary.
+    - `000_migration.sql` — contains ONLY the creation of the migrations
+      tracking table itself. Nothing else.
+    - `001_schema.sql` — the full application schema.
+    - **Pre-1.0.0:** never add additional migration files (002, 003, etc.).
+      There is no installed base to migrate. Edit `001_schema.sql` directly.
+    - **Post-1.0.0:** add new numbered migration files for each schema change.
+      Never edit existing migrations after release.
 
 - All repos should have an `.editorconfig` enforcing the project's indentation
   settings.