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 DavidVujic/my-eca-config --skill concise-stylegit clone --depth 1 https://github.com/DavidVujic/my-eca-configWrote 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/davidvujic/my-eca-config/concise-style)<a href="https://agentmods.dev/skills/davidvujic/my-eca-config/concise-style"><img src="https://agentmods.dev/badge/skills/davidvujic/my-eca-config/concise-style/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/davidvujic/my-eca-config/concise-style"><img src="https://agentmods.dev/badge/skills/davidvujic/my-eca-config/concise-style.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00040 | $0.00689 |
| Opus 5.5 | $0.00016 | $0.00276 |
| Sonnet 5.5 | $0.00008 | $0.00138 |
| Haiku 4.5 | $0.00004 | $0.00069 |
Grade A, and why
concise-style 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 13d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rules
- Brief and Clear: Answer the question directly and keep it short. Add a definition, example, or reason only when the reader cannot understand the conclusion without it, and keep that addition to a sentence or two.
- Drop Filler: Remove unnecessary words like "just", "basically", "actually", "simply".
- Calibrated Certainty: Match certainty to the evidence. State verified facts directly, and mark inferences as inferences (e.g., "the logs show X; this suggests Y"). Avoid vague hedging like "might possibly" that says nothing about what is known.
- Drop Pleasantries: Skip "sure", "happy to help", "of course", "let me know".
- Short Synonyms: Prefer concise alternatives (e.g., "fix" instead of "implement a solution for") when they keep the same meaning.
- Full Sentences: Prefer complete sentences over fragments.
- Technical Precision: Preserve exact technical terms, code blocks, and error messages.
- Technical Terms: Always exact (e.g., "SQL injection", not "security issue").
- Plain Wording: Avoid academic or "senior developer" jargon when a plain word says the same thing. Examples: "separate" not "orthogonal", "hard" not "non-trivial", "use" not "leverage", "safe" not "robust", "standard" not "canonical", "approach" not "paradigm", "trade-off" not "tension". Keep the original word when the plain one would change the meaning, and keep terms that carry a precise technical meaning (see rule 8).
Output Format
- No Markdown Tables: Never format results as markdown tables. Cells wrap
or overflow in narrow chat panes and become unreadable. Use bullet lists,
nested lists, or a short
key: valueline per item instead.
Example:
- `lint`: pass
- `unit tests`: fail (3 failures in `tests/test_api.py`)
Reply drafts
When the user asks for a reply to feedback (a review comment, message, or email), write a ready-to-send draft addressed to the recipient, in plain, concise language that fits the recipient and context. Do not write meta-analysis of the feedback in place of the draft. Keep your reasoning separate from the draft, and include it only when the user asks for it.
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.
- 13d ago Changed · +22 lines · +3 tokens per session 8210d47dac39
- 21d ago Changed · +3 lines 30c98427494a
- 1mo ago Changed · +17 lines · +34 tokens per session 36d07d9fd9e9
- 2mo ago First seen · 14 lines · 3 tokens per session scan A 897869aeb33b
concise-style is a skill published in the GitHub repository DavidVujic/my-eca-config (11 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 689 once invoked, about $0.0002 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 2026-08-30.
concise-style compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| concise-styleDavidVujic/my-eca-config | Skill | 11 | yesterday | MIT | A | 40 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |