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 sergeyklay/.agents --skill make-skillgit clone --depth 1 https://github.com/sergeyklay/.agentsWrote 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/sergeyklay/.agents/make-skill)<a href="https://agentmods.dev/skills/sergeyklay/.agents/make-skill"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/make-skill/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/sergeyklay/.agents/make-skill"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/make-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Prompt Injection · line 87 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 222 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00080 | $0.03546 |
| Opus 5.5 | $0.00032 | $0.01418 |
| Sonnet 5.5 | $0.00016 | $0.00709 |
| Haiku 4.5 | $0.00008 | $0.00355 |
Grade A, and why
make-skill 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 1mo 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating Agent Skills
Author Agent Skills against the agentskills.io specification. A skill is a self-contained directory of instructions, scripts, and resources that turns a general-purpose agent into a specialist for one focused domain.
Core Philosophy
Context is shared. Your skill's tokens compete with the system prompt, conversation history, other skills, and the user's request. Once SKILL.md loads it stays in context for the rest of the turn. Every line must earn its place.
The agent is already smart. Add only context it lacks. Cut explanations of well-known concepts (PDFs, for-loops, HTTP, JSON) and any sentence whose absence would not confuse a competent agent.
Reason over command. Prefer "Use pdfplumber because it handles multi-column layouts and rotated text better than alternatives" to "ALWAYS use pdfplumber". The reasoning becomes the rubric for cases the skill did not anticipate.
Write for the agent, not the human reader. The audience is an LLM ingesting tokens, not a person browsing a wiki page. Optimize for density and clarity, not visual aesthetics. Visual decoration — hard wraps that imply meaningful line breaks, blockquotes around examples, redundant "why this works" paragraphs after every code block, three-deep ladders of indented bullets, decorative Tip:/Note: wrappers around single sentences — costs tokens and earns nothing. See references/writing-patterns.md § Density for dense-vs-decorative examples.
Skill Anatomy
skill-name/
├── SKILL.md # required: YAML frontmatter + markdown body
├── scripts/ # optional: executable code; output enters context
├── references/ # optional: docs loaded on demand
├── assets/ # optional: templates, schemas, images
└── agents/ # optional: per-vendor sidecars, e.g. Codex's openai.yaml
Only SKILL.md is required. Drop empty directories. agents/ holds vendor sidecar config rather than skill content; its one current occupant is Codex's agents/openai.yaml, described in references/frontmatter-fields.md.
What ships with it
8 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.
- references/anti-patterns.md 3.6 KB
- references/frontmatter-fields.md 25 KB
- references/platform-targeting.md 5.2 KB
- references/reviewing-skills.md 2.0 KB
- references/skills-ecosystem.md 6.2 KB
- references/writing-patterns.md 14 KB
- scripts/init_skill.py 3.8 KB runs code
- scripts/validate_skill.py 27 KB runs code
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.
- 1mo ago Changed · -4 tokens per session eca5af088602
- 1mo ago Changed · +1 lines 1646145716d1
- 1mo ago Changed · -72 lines 5aec06a51c33
- 1mo ago Changed · +2 lines df31b72a5608
- 1mo ago First seen · 319 lines · 84 tokens per session scan A b0bfe3bfa48d
make-skill is a skill published in the GitHub repository sergeyklay/.agents (6 stars, last pushed 5d ago), licensed Apache-2.0. It adds 80 tokens to every session and 3,546 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
autodoc-next-prospectus-audit
Audit one local prospectus PDF, DOC, or DOCX through PDRouter and download the annotated document with AutoDoc NEXT2.0.
ChatDOC Studio--KnowledgeMate
Create and operate ChatDOC Studio knowledge bases through pdrouter using a Bearer API key and JavaScript helpers. Use when Codex needs to upload one or more PDF/DOC/DOCX files, skip failed files without aborting the whole job, create a knowledge base from successful uploads, or call the ChatDOC Studio knowledge-base…
PDFlux-PDF2Markdown
Convert unstructured documents into LLM-ready structured data. Supports PDF, Word, PPT, and images; extracts paragraphs, formulas, tables, charts, and other elements in one step; generates up to 8 levels of headings; and outputs Markdown organized in reading order. Useful for field extraction, comparison and…
Calliper-Compare2Markdown
Compare two local documents and convert differences into LLM-ready Markdown in one synchronous call. Supports PDF, Word, PPT, and image documents accepted by Calliper, and returns a structured markdown diff table suitable for change review, clause comparison, downstream extraction, and rule-based validation.
war-room
Multi-agent research war room. Personas debate in sequential turns through two phases — ideation and proposal writing. Persona persistence and drift detection are enforced every turn via the persistent-persona skill.
system-info
Probe system resources — CPU, RAM, disk, GPU/CUDA/MPS — and translate findings into experiment design recommendations. Run this at the start of any compute-intensive project.