Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/tellahq/opensession/unslopnpx skills add tellahq/opensession --skill unslopgit clone --depth 1 https://github.com/tellahq/opensessionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tellahq/opensession/unslop)<a href="https://agentmods.dev/skills/tellahq/opensession/unslop"><img src="https://agentmods.dev/badge/skills/tellahq/opensession/unslop.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00014 | $0.01619 |
| Opus 5 | $0.00007 | $0.00809 |
| Sonnet 5 | $0.00003 | $0.00324 |
| Haiku 4.5 | $0.00001 | $0.00162 |
Grade A, and why
unslop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- unslop — 100% identical, 33 lines differ
- unslop — 100% identical, 4 lines differ
- unslop — 100% identical, 0 lines differ
- unslop — 100% identical, 0 lines differ
- unslop — 100% identical, 0 lines differ
- unslop — 100% identical, 0 lines differ
- unslop — 100% identical, 0 lines differ
- unslop — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unslop
Edit text to remove AI patterns and add human voice.
Process
- Scan for the patterns below.
- Rewrite. Preserve meaning, match intended tone.
- Add soul (see next section).
- Self-audit: "What makes this obviously AI generated?" Fix remaining tells.
Adding soul
Removing patterns is half the job. Sterile, voiceless writing is just as obvious.
- Have opinions. React to facts instead of neutrally listing pros and cons.
- Vary rhythm. Short sentences. Then longer ones that take their time. Mix it up.
- Acknowledge complexity. "Impressive but also kind of unsettling" beats "impressive."
- Use "I" when it fits. First person isn't unprofessional.
- Let some mess in. Perfect structure looks machine-made.
- Be specific. Not "this is concerning" but "there's something unsettling about agents churning away at 3am."
Patterns to detect and fix
Content
- Puffery. "pivotal moment", "testament to", "evolving landscape", "setting the stage for", "indelible mark", "deeply rooted". Cut puffery, state what happened.
- Name-dropping. Listing media outlets without context. Pick one, say what was said.
- Superficial -ing phrases. "highlighting...", "ensuring...", "reflecting...", "showcasing...", "fostering...". Delete or expand with real sources.
- Promotional language. "nestled", "vibrant", "breathtaking", "groundbreaking", "renowned", "stunning", "must-visit". Use neutral descriptions.
- Vague attributions. "Experts believe", "Industry reports suggest", "Some critics argue". Name the source or delete.
- Formulaic challenges. "Despite challenges... continues to thrive." Replace with specific facts.
Language
- AI vocabulary. Additionally, crucial, delve, enduring, enhance, fostering, garner, interplay, intricate, landscape (abstract), pivotal, showcase, tapestry (abstract), testament, underscore, vibrant. Replace with plain words.
- Fancy ways to say "is". "serves as", "stands as", "boasts", "features". Just say "is" or "has".
- "Not just X, but Y." State the point directly instead.
- Rule of three. Forcing ideas into groups of three. Use the natural number.
- Synonym cycling. Protagonist, main character, central figure, hero all in one paragraph. Pick one, repeat it.
- False ranges. "from X to Y" where X and Y aren't on a meaningful scale. List topics directly.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 81 lines · 14 tokens per session scan A 181883e539ca
unslop is a skill published in the GitHub repository tellahq/opensession (345 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 1,619 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…