anti-slop
Skill1 starsChanged 4 months agoMITView on GitHub
Fast first-pass reality check for any codebase -- especially vibe-coded / LLM-generated projects friends hand you to "look over." Answers the only question that matters up front: is this real software, or a confident-looking mirage? Produces a one-page VERDICT with a 0-100 Substance Score, top red flags, a go/no-go call, and an ordered fix roadmap -- backed by per-topic evidence on disk. Three layers over one engine: (1) universal slop checks that apply to any language, (2) a language pack (TypeScript/JS and Python implemented; Go/Rust stubbed) that runs the real toolchain, (3) optional domain packs (crypto-wallet bundled). Use this skill when the user says "audit this", "is this real / any good", "check this project", "anti-slop", "slop check", "review this repo", "did they actually build it", "should I bother", "vibe check this", or hands over an unfamiliar repo to vet. This is the first thing you run on any project before a deeper domain audit.
31 other projects use a version of this.
Adopted by
Most recently taken up by
- MishraShardendu22/agent-skills-hub-sync-enginetheir own version, first seen Nov 8, 2026
- TheVeller/claude-skillstheir own version, first seen Nov 8, 2026
- a7garden/anti-sloptheir own version, first seen Nov 8, 2026
- umfhero/skillstheir own version, first seen Nov 8, 2026
- Vumb-VibeCoder/hook-everythingtheir own version, first seen Nov 8, 2026
- adeonir/agent-skillstheir own version, first seen Nov 6, 2026
Used with
Projects with it also use research.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
NVIDIASkillresearch
Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.
Also in 3 projects that use this
Other versions31 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 31
- elithrar/dotfiles★ 222same name
- Gesso-Build/skills★ 91same name
- roedyrustam/vibes-plug★ 75same name
- Tom-Babb/ai-marketing-skills-with-by-tom-babb★ 30same name
- Vumb-VibeCoder/hook-everything★ 19same name
- aixarizzo/kill-slop★ 17same name
- darknecrocities/SkillBuilder★ 13same name
- HyunjunJeon/claude-workflow-mods★ 9same name
- taljeon/plzdo★ 9same name
- YuliangXiu/de-ai-router★ 9same name
21 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
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- retroSkill
- rust-conventionsSkill
- scrub-ai-tellsSkill
- skill-distillSkill
- tixSkill
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- typescript-conventionsSkill
The file
We split this skill into the rules it gives an agent
9 rules. 0 are common, 3 are distinctive, and 6 are very specific to this project.
0
Common
Most of the 30 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 72
Every subagent gets this wrapper (fill in <id> and <REPO>):
- Very specific: line 82
Run u01_inventory_stack first and wait.
- Distinctive: line 85
Read that file -- every later decision keys off it.
- Very specific: line 121
After all topic findings exist and before synthesis, run one severity_normalize agent.
- Very specific: line 134
Read every file in .antislop/findings/ AND .antislop/evidence/severity_normalized.md, then write .antislop/VERDICT.md following …
- Very specific: line 143
If --deep or --domain <name>: copy that pack's prompts into .antislop/prompts/ and run them as an extra wave, then fold their findings into …
- Distinctive: line 163
Default model: Sonnet for universal/language waves.
- Very specific: line 165
If u01 fails, stop -- every later topic depends on the stack map.
- Distinctive: line 167
Never fabricate a finding to fill a topic.
“Common” is measured: kept by at least 6 in 10 of the 30 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Anti-Slop: First-Pass Reality Check
You are the orchestrator. You coordinate subagents -- you do not review code yourself. Each subagent has its own isolated context, reads one prompt file, does the analysis, and writes findings to disk. Your job is setup, scheduling, and synthesis.
This is a triage tool. The deliverable people actually read is the one-page VERDICT.md.
Everything else is backing evidence for when someone disputes the call. Optimize for a
2-minute read that ends in a clear "real / fix it / restart" decision.
Prompt files live in references/ inside this skill and are copied to .antislop/prompts/
in the target repo during setup. Findings are written to .antislop/findings/.
Arguments
Parse from the user's invocation:
--quick-- universal layer only (skip the language pack). Fastest triage.--deep-- after the verdict, also run the matched domain pack (default: recommend, don't run).--domain <name>-- force a specific domain pack (e.g.crypto-wallet).--lang <name>-- force a language pack instead of auto-detecting.--topic <id>-- run only one topic (e.g.u03_stubs_dead_code).--setup-- initialize dirs and copy prompts only; spawn nothing.--no-score-- skip the numeric Substance Score (still produce the verdict).--resume-- skip topics whose findings files already exist.--dry-run-- print the plan only; write nothing; spawn nothing.
Step 1: Setup
REPO=$(git rev-parse --show-toplevel 2>/dev/null || pwd)
# Locate this skill's references/. NOTE: some environments wrap `find` with `bfs`,
# whose `-path` glob does not match -- so check canonical locations directly, then fall
# back to a `-name` search (which traverses reliably) filtered to anti-slop.
SKILL_DIR=""
for base in "$HOME/.claude/skills" "$REPO/.claude/skills"; do
[ -d "$base/anti-slop/references" ] && { SKILL_DIR="$base/anti-slop/references"; break; }
done
[ -z "$SKILL_DIR" ] && SKILL_DIR=$(find "$HOME/.claude" "$REPO/.claude" -type d -name references 2>/dev/null | grep anti-slop | head -1)
mkdir -p "$REPO/.antislop/"{prompts,findings,evidence}
git -C "$REPO" rev-parse HEAD > "$REPO/.antislop/COMMIT_SHA.txt" 2>/dev/null || echo "no-git" > "$REPO/.antislop/COMMIT_SHA.txt"
if [ -n "$SKILL_DIR" ]; then
cp "$SKILL_DIR"/_engine/*.md "$REPO/.antislop/prompts/"
cp "$SKILL_DIR"/universal/*.md "$REPO/.antislop/prompts/"
echo "Copied engine + universal prompts."
else
echo "WARNING: could not find anti-slop references. Prompts may already be in .antislop/prompts/."
fiLanguage-pack prompts are copied in Step 3 after the stack is known. If --setup: stop here.
Every subagent gets this wrapper (fill in <id> and <REPO>):
You are running a focused, read-only reality check on the codebase at
<REPO>. Read your prompt at<REPO>/.antislop/prompts/<id>.mdand follow it exactly. Also read<REPO>/.antislop/prompts/shared_rules.mdand<REPO>/.antislop/prompts/findings_schema.mdfirst. Use absolute paths under<REPO>. Do NOT modify source, commit, install, or deploy. Write your findings to<REPO>/.antislop/findings/<id>.mdusing the Write tool before finishing.
Step 2: Wave 0 -- Inventory & Stack Detection (sequential)
Run u01_inventory_stack first and wait. It maps the repo and writes
.antislop/evidence/stack.md declaring: detected language(s), package manager(s), frameworks,
app surfaces, and a domain guess (e.g. crypto-wallet, web-api, cli, unknown).
Read that file -- every later decision keys off it.
Step 3: Pick & copy the language pack
From stack.md's toolchain_for_language_pack, choose the pack (see
references/lang/_stack_detect.md):
- TypeScript / JavaScript →
lang/ts/(implemented) - Python →
lang/py/(implemented) - Go / Rust → stubbed; if matched, tell the user the pack isn't built yet and run universal-only, noting the gap in the verdict. Do not fabricate language-specific findings.
- Polyglot repo → copy each implemented pack that applies and label findings by sub-project.
LANG=$(rg -m1 '^toolchain_for_language_pack:' "$REPO/.antislop/evidence/stack.md" | sed 's/.*: *//' | tr -d ' ')
for l in $(echo "$LANG" | tr ',' ' '); do
[ -d "$SKILL_DIR/lang/$l" ] && cp "$SKILL_DIR"/lang/$l/*.md "$REPO/.antislop/prompts/" && echo "Copied $l language pack."
doneSkip this step entirely if --quick.
Step 4: Wave 1 -- Universal slop checks (parallel)
Spawn all eight in parallel:
u02_docs_vs_reality, u03_stubs_dead_code, u04_secret_hygiene, u05_dependency_sanity,
u06_config_env_prod, u07_ci_repo_hygiene, u08_architectural_coherence, u09_error_handling
Step 5: Wave 2 -- Language pack (parallel, skipped on --quick)
Spawn the three topics of each matched pack (e.g. TS: ts01_build_types_lint,
ts02_test_reality, ts03_runtime_safety; Python: py01_build_types_lint,
py02_test_reality, py03_runtime_safety). These run the real toolchain (tsc/eslint/jest,
mypy/ruff/pytest) and are the ground truth for "does it actually work."
Step 6: Wave 2.5 -- Severity Normalization (sequential, single agent)
After all topic findings exist and before synthesis, run one severity_normalize agent.
Per-topic agents grade BLOCKER/HIGH/MEDIUM in isolation, so their calls drift -- and that drift
is what moves a repo across the Go/No-Go line. This pass re-grades every consequential finding
against one bar (references/_engine/severity_rubric.md, copied to prompts/) with full
cross-topic visibility, applying the reachability test (untrusted-reachable RCE/auth-bypass/
fund-movement = BLOCKER; trusted-local-operator-only = capped at MEDIUM). It writes
.antislop/evidence/severity_normalized.md with reconciled tallies and a Go/No-Go driver.
Skip only if --no-score AND the user explicitly wants raw grades. For scale, you may run a
3-agent panel and take the majority grade per finding instead of one normalizer.
Step 7: Wave 3 -- Synthesis → VERDICT.md (sequential)
Read every file in .antislop/findings/ AND .antislop/evidence/severity_normalized.md,
then write .antislop/VERDICT.md following references/_engine/verdict_template.md exactly.
Compute the Substance Score per the rubric there (unless --no-score). Use the normalized
severities -- not the raw per-topic grades -- for the blocker count, Go/No-Go, and red-flag
ranking. The verdict leads; evidence is indexed, not pasted.
Step 8: Domain handoff
From stack.md's domain guess, consult references/domain/_registry.md:
- If
--deepor--domain <name>: copy that pack's prompts into.antislop/prompts/and run them as an extra wave, then fold their findings into the verdict. - Otherwise: end the verdict with a one-line recommendation of which domain pack to run
next and the exact command (e.g.
/anti-slop --deep --domain crypto-wallet).
Step 9: Completion report
ANTI-SLOP -- <repo name> @ <sha>
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SUBSTANCE SCORE <n>/100 → <Real | Mostly-real | Mirage | Abandon>
RED FLAGS <n> BLOCKERS <n>
Verdict written: .antislop/VERDICT.md
Recommended next: <domain pack or "none">
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Print the one-paragraph verdict inline so the user gets the answer without opening a file.
Notes for the Orchestrator
- Default model: Sonnet for universal/language waves; Opus for synthesis. Override as needed.
- Tell the user which agents are about to run before each wave; one-line PASS/FAIL after.
- If
u01fails, stop -- every later topic depends on the stack map. --resume: skip topics whose.antislop/findings/<id>.mdalready exists; mark "RESUMED".- Never fabricate a finding to fill a topic. INCONCLUSIVE is an honest verdict.
- Three layers, one engine: universal (
references/universal/) is language- and domain-agnostic; language packs (references/lang/<lang>/) own the toolchain; domain packs (references/domain/<name>/) own domain risk. All share_engine/rules + schema + verdict format. To add a language or domain, drop a new folder in -- the orchestrator picks it up.
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