Borrowing it
Nothing to install: this file belongs to loerei/chronicle-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/loerei/chronicle-mcp/main/.agents/skills/write-for-ai/SKILL.mdgit clone --depth 1 https://github.com/loerei/chronicle-mcpWrote 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/loerei/chronicle-mcp/write-for-ai)<a href="https://agentmods.dev/skills/loerei/chronicle-mcp/write-for-ai"><img src="https://agentmods.dev/badge/skills/loerei/chronicle-mcp/write-for-ai/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/loerei/chronicle-mcp/write-for-ai"><img src="https://agentmods.dev/badge/skills/loerei/chronicle-mcp/write-for-ai.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 | $0.00026 | $0.01694 |
| Opus 5 | $0.00013 | $0.00847 |
| Sonnet 5 | $0.00005 | $0.00339 |
| Haiku 4.5 | $0.00003 | $0.00169 |
Grade A, and why
write-for-ai 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 3d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write for AI
Text written for AI must directly drive decisions, constraints, or routing. It should never market, reassure, speculate, or over-explain.
The Two Deslop Vectors
Vector 1: De-fluffing (Jargon Elimination)
Strip pompous phrasing, marketing fluff, and pseudo-technical vocabulary. Replace with direct, plain English.
- Cut marketing adjectives & adverbs:
robust,seamless,powerful,smart,intelligent,best-in-class,safely. - Cut pseudo-technical buzzwords:
orchestrate,leverage,facilitate,paradigm,synergy. - Cut self-important titles: Replace grandiose section headers with simple nouns ("Workflow").
- Use simple, active verbs: Prefer
get,set,run,check,edit,deleteover Latinate verbs.
Vector 2: De-overexplaining (Redundancy Elimination)
Strip information the AI already knows, cannot act upon, or that duplicates existing definitions. Target the 6 universal forms of redundancy:
- Schema & Location Duplication: Repeating types, default values, enums, or layout rules already defined in parameter schemas or global configs.
- Tautology / Circular Naming: Explaining what the identifier, tool name, or section title already makes obvious (e.g.,
# Tool delete_user->"This tool deletes a user"). - Conversational Chaff & Hedging: Polite filler, introductory padding, and weak modals (
"Please note that you should try to..."). Replace with direct imperatives (MUST,NEVER). - Motivational & Historical Justification: Explaining why a feature was built, its architectural history, or how much time/tokens it saves.
- Synonym Stacking: Chaining redundant synonyms and qualifiers (
"strict, absolute, mandatory, and non-negotiable boundary"). - Reference Over-Specification: Explaining, summarizing, or itemizing the sub-topics, case studies, or internal contents of a referenced document inside the link sentence (e.g., write
see [REFERENCE.md](REFERENCE.md)instead ofsee [REFERENCE.md](REFERENCE.md) (Topic A, Topic B, Topic C)).
What ships with it
1 file 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.
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.
- 3d ago Changed · +1 lines 7ae326faa629
- 5d ago First seen · 76 lines · 26 tokens per session scan A d1991bb3251f
write-for-ai is a skill published in the GitHub repository loerei/chronicle-mcp (0 stars, last pushed 4d ago), licensed MIT. It adds 26 tokens to every session and 1,694 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.
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