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 skills add gohypergiant/agent-skills --skill accelint-english-managergit clone --depth 1 https://github.com/gohypergiant/agent-skillsWrote 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/gohypergiant/agent-skills/accelint-english-manager)<a href="https://agentmods.dev/skills/gohypergiant/agent-skills/accelint-english-manager"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/accelint-english-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gohypergiant/agent-skills/accelint-english-manager"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/accelint-english-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 189 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 5.1 | $0.00216 | $0.04236 |
| Opus 5 | $0.00108 | $0.02118 |
| Sonnet 5 | $0.00043 | $0.00847 |
| Haiku 4.5 | $0.00022 | $0.00424 |
Grade A, and why
accelint-english-manager 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 12d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.
English Manager
Use plain, direct English that is easy to read, easy to scan, and easy to act on.
Do not optimize for brevity alone. Preserve the user's intended meaning, audience, tone, and explicit constraints while making the text clearer, steadier, and harder to misread.
This skill uses one default writing system:
- plain-language discipline for direct, concrete wording
- STE-leaning structure for technical clarity and stable terminology
- ADHD-friendly shaping for scanability and actionability when the text helps someone do something
Use these together. They are not separate modes.
Hard constraints
These outrank style preferences.
- Preserve the user's meaning before you optimize wording.
- Preserve the requested tone, audience fit, and explicit format constraints.
- Preserve deliberate warmth, rhythm, humor, persuasion, or brand voice when the user wants them.
- Preserve code, identifiers, commands, file paths, quoted errors, product names, API names, config keys, and legal text unless the user explicitly asks to rewrite them.
- Keep real uncertainty, real nuance, and real obligation levels. Do not make text sound simpler by making it less true.
- Do not claim official ASD-STE100 compliance. If the user asks for strict STE, say that full compliance depends on the official standard and dictionary.
Start here
Choose the smallest fitting path before you edit.
Step 1: Ask for the mode first
Do this first for drafting or rewriting tasks unless the user already specified the mode explicitly.
Offer these choices:
mode=default— local rewrite by default, plain and directmode=strict— stricter technical control, structural rewrite allowed when needed
If the user did not choose a mode, ask a short clarifying question instead of assuming. Done when: the rewrite mode is explicit, or the request is clearly audit-only.
Step 2: Choose the output mode
Requires: Step 1 is complete when the request needs a rewrite mode.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- CHANGELOG.md 7.5 KB
- evals/evals.json 31 KB
- README.md 7.4 KB
- references/adhd-patterns.md 3.0 KB
- references/checklist.md 3.5 KB
- references/examples.md 6.1 KB
- references/rfc-2119.md 2.2 KB
- references/serial-instruction-guidance.md 4.8 KB
- references/ste-rules.md 9.2 KB
- references/substitutions.md 4.7 KB
- references/use-cases.md 3.6 KB
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.
- 12d ago First seen · 386 lines · 216 tokens per session scan A 55ac6ed81b44
accelint-english-manager is a skill published in the GitHub repository gohypergiant/agent-skills (24 stars, last pushed 2d ago), licensed Apache-2.0. It adds 216 tokens to every session and 4,236 once invoked, about $0.0011 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 2026-08-30.
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