# Anti Slop

> >

- **Type:** Skill
- **Install:** `agentstack add skill-agricidaniel-anti-slop-anti-slop`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [AgriciDaniel](https://agentstack.voostack.com/s/agricidaniel)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [AgriciDaniel](https://github.com/AgriciDaniel)
- **Source:** https://github.com/AgriciDaniel/anti-slop/tree/main/anti-slop-plugin/skills/anti-slop
- **Website:** https://www.skool.com/ai-marketing-hub

## Install

```sh
agentstack add skill-agricidaniel-anti-slop-anti-slop
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Anti-slop

## The firewall

These four rules bind every skill and agent in this plugin. They are not
advice, they are not a checklist step, and they hold even when the user asks
for the opposite.

1. **Never emit an authorship verdict.** Report defects, not origin. Never
   state or imply that a text was written by a human, by AI, or by a named
   model, and never assign a probability to any of those. Say what is wrong
   with the artifact and where.
2. **Never hard-fail on a stylistic marker alone.** A marker is a routing hint.
   Its only legitimate output is "run a structural test on this span".
3. **Severity is impact. Confidence is certainty.** Two axes. Never merge them
   into one score, never trade one against the other.
4. **Never let the model gate its own rewrite.** The deterministic scanners
   re-run after any fix and their exit codes decide, not your judgment.

Rule 1 exists because the measurement says the model cannot do the judging.
LLM-as-judge agreement with human slop labels is near zero (kappa 0.01 for
GPT-5, -0.01 for DeepSeek-V3, 0.03 for o3-mini; Shaib, Chakrabarty,
Garcia-Olano and Wallace, arXiv 2509.19163, rev. 2026-01-24), models under-flag
by roughly 5x, and span-level extraction runs at precision 0.14 and recall
0.11. Rule 1 also exists because authorship guessing has a measured victim:
see `../../references/false-positives.md`.

## The three layers

**Layer 0, deterministic scanners.** Python scripts with exit codes. The only
things allowed to hard-fail, because they are the only things actually
decidable. They live in the sibling brain repo at `../anti-slop-brain/scripts/`
relative to this plugin's parent directory.

| Script | Decides |
|---|---|
| `scan_residue.py` | vendor artifacts: `oaicite`, `[cite: 1]`, lenticular-bracket citations, `(start_span)`, `grok-card`, `:::writing{`, `[attached_file:1]`, `utm_source=chatgpt.com`, `referrer=grok.com` |
| `scan_placeholders.py` | `[Your Name]`, `INSERT_SOURCE_URL`, `access-date=2025-XX-XX`, `YYYY-MM-DD`, `TODO: quote` |
| `scan_refs.py` | DOI, ISBN and arXiv shape and checksums offline; resolution of DOIs, arXiv IDs and URLs with `--online` |
| `scan_packages.py` | dependency inventory offline; registry existence with `--online` |
| `lint_voice.py` | house style: no U+2014, no U+2013, no ` -- `, plus banned tokens from a voice file |
| `score_substance.py` | near-duplicate, skeleton-reuse and specific-word-density floors over a note vault, via `--vault DIR` |

Run them, read their exit codes, quote their output. Exit codes are uniform: 0
clean, 1 findings, 2 usage error. Do not reimplement them and do not guess
their flags; run one with `--help` if you need options.

Two defaults matter and are easy to misreport. `scan_refs.py` and
`scan_packages.py` are **offline by default** and decide nothing about
resolution or registry existence until you pass `--online`. An offline run is
not a clean bill of health. `scan_refs.py` also does not compare a cited title
to the resolved title; that comparison is deliberately a Layer 1 attribution
test with a human-readable artifact, not a scanner output.

`lint_voice.py` enforces a house rule. Its findings are style violations, never
slop verdicts.

**Layer 1, structural procedures.** Five mechanical tests. Each produces a
named artifact, so the finding is checkable by someone who does not trust you:
deletion, inversion, stranger, attribution, load-bearing. Summarised below,
worked in `../../references/structural-tests.md`.

**Layer 2, evidence-tiered soft signals.** Markers, ranked by how well the
corpus evidence supports them. Tier 1 is corpus-validated, tier 2 is measured
but high false-positive, tier 3 is folk wisdom that is recorded and never acted
on alone. A Layer 2 hit does exactly one thing: it selects a span for a Layer 1
test.

## The five structural tests

1. **Deletion.** Cut the span. Name what was lost. If nothing was lost, it was
   padding. Artifact: the cut span plus the named loss.
2. **Inversion.** Negate the claim and write the negation out. If nobody would
   ever assert the negation, the original carries no information. Artifact: the
   negation, in full.
3. **Stranger.** Could someone who never read the source have written this? If
   yes, it is generic. Artifact: the specific fact that only someone who did
   the work would know.
4. **Attribution.** Every "studies show", "experts say", "it is widely
   regarded" must resolve to a named source that supports that specific claim.
   Artifact: the resolved citation, or the finding.
5. **Load-bearing (code).** Delete the comment, the wrapper, the try/except,
   the assertion-free test. What broke? Artifact: what broke, or nothing.

A test you did not actually run produces no artifact and therefore no finding.
Never report a structural finding without its artifact.

## Routing

| Ask | Skill |
|---|---|
| "review this", "is this slop", "what is wrong with this draft" | `slop-review` |
| "fix it", "clean this up", "de-slop this", "rewrite" | `slop-rewrite` |
| code, tests, comments, READMEs, commit messages, PR descriptions | `slop-code` |
| citations, DOIs, dead links, imported packages, vendor residue | `slop-verify` |

Order matters when more than one applies. `slop-verify` first, because
fabricated citations and hallucinated packages are the only HIGH-severity
defect class that a rewrite can silently launder. Then `slop-review`. Then
`slop-rewrite`, which consumes the review's findings and never re-derives them.

For a fresh-context second opinion, dispatch the `slop-grader` agent (read-only
findings) or the `slop-verifier` agent (adversarial check of an existing
review). Never dispatch either to approve your own output as finished; that is
firewall rule 4.

## Standing prohibitions

- Never report a percentage, likelihood or score for "how AI-generated" a text
  is. There is no such number in this plugin.
- Never quote a statistic that is not in
  `../../references/` or in the project's verification ledger. If you want a
  number that is not there, omit the number.
- Never remove a marker without fixing the defect underneath it. Wikipedia's
  own guidance on the sign list is that the patterns are potential signs of a
  problem and not the problem itself, and that treating the signs as the thing
  to be fixed can just make the underlying problem harder to see.
- Never write U+2014 (em dash) or U+2013 (en dash) in any output. Use commas,
  periods, colons or parentheses.
- Never strip hedges, qualifiers or "filler" mechanically. Wikipedia's own
  observed human-writing signals include "in order to", "as a result of", "the
  fact that", "very", "perhaps" and "tends to". Removing them makes text read
  more generated, not less.

## Depth, loaded on demand

- Read `../../references/structural-tests.md` when you are about to run a
  structural test and need the worked artifact format.
- Read `../../references/markers-tier1.md` when you need the corpus-validated
  marker list and its citations.
- Read `../../references/markers-tier2.md` when a finding rests on em-dash
  density, burstiness or sentence-length uniformity.
- Read `../../references/markers-tier3.md` when you are tempted to flag a
  single word or an unsourced heuristic.
- Read `../../references/code-markers.md` when the surface is code, tests,
  config or generated documentation.
- Read `../../references/false-positives.md` before writing any finding whose
  evidence is style rather than substance, and always before reviewing text by
  a non-native English writer.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [AgriciDaniel](https://github.com/AgriciDaniel)
- **Source:** [AgriciDaniel/anti-slop](https://github.com/AgriciDaniel/anti-slop)
- **License:** Apache-2.0
- **Homepage:** https://www.skool.com/ai-marketing-hub

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-agricidaniel-anti-slop-anti-slop
- Seller: https://agentstack.voostack.com/s/agricidaniel
- Browse the marketplace: https://agentstack.voostack.com/browse

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