Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/serejaris/kimi-skillsnpx agentmods add skills/serejaris/kimi-skills/essayWrote 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/serejaris/kimi-skills/essay)<a href="https://agentmods.dev/skills/serejaris/kimi-skills/essay"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/essay/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/serejaris/kimi-skills/essay"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/essay.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 | $0.00055 | $0.02543 |
| Opus 5 | $0.00028 | $0.01272 |
| Sonnet 5 | $0.00011 | $0.00509 |
| Haiku 4.5 | $0.00006 | $0.00254 |
Grade A, and why
essay 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 9d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Essay Writing
Orchestrator dispatches all creation and review work to subagents. Before creation, copy user-uploaded files to /mnt/agents/output/research/.
Sub-skill of general-writing. Inherits shared creative writing principles, anti-AI discipline, and quality gate framework.
CRITICAL — Review → Fix Brief → Dispatched Subagent: When a review finds issues, translate them into a detailed fix brief (file paths, quoted findings, expected outcome, scope boundary, self-check) and dispatch a fresh
essay_writersubagent to apply the fix. Never use inline sed/edit_file fixes.
CRITICAL — Anti-Read-Loop Rule: The orchestrator must dispatch its first subagent (essay_writer) within 10 iterations. If the orchestrator has spent 10+ iterations only reading files without creating any subagent, it is in a read-loop. Stop reading, draft your conception from what you have, and dispatch the writer immediately.
CRITICAL — .docx Delivery: Every completed essay must be converted to .docx using
skills/docx/SKILL.md. Never end a session with raw .md files and no .docx deliverable.
File Paths
Output: /mnt/agents/output/
{project_name}.essay.md # Final essay
research/ # User uploads (source material, references)
Trigger Keywords
散文, 随笔, essay, personal essay, 杂文, prose, 小品文, 议论文, 抒情散文, 叙事散文, op-ed, 评论, commentary, reflection, thought leadership, 洞见, insight essay, 公众号文章, 小红书
Workflow Decision Tree
User Query
│
├─ Provides draft + asks for revision → Stage 3 → Stage 4
├─ Specifies type/theme clearly → Stage 1 → Stage 2 → Stage 3 → Stage 4
└─ Vague request → Infer parameters (see below) → Stage 1 → Stage 2 → Stage 3 → Stage 4
Infer essay type, audience, platform, length, and language from the user's request. The orchestrator analyzes and infers all parameters autonomously; for complex requests, deploy a subagent to analyze requirements in depth. Never prompt the user for clarification.
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.
- 9d ago First seen · 202 lines · 55 tokens per session scan A 1c77df857d02
essay is a skill published in the GitHub repository serejaris/kimi-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 2,543 once invoked, about $0.0003 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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