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 hassancs91/content-factory-starter --skill content-factorygit clone --depth 1 https://github.com/hassancs91/content-factory-starterWrote 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/hassancs91/content-factory-starter/content-factory)<a href="https://agentmods.dev/skills/hassancs91/content-factory-starter/content-factory"><img src="https://agentmods.dev/badge/skills/hassancs91/content-factory-starter/content-factory/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/hassancs91/content-factory-starter/content-factory"><img src="https://agentmods.dev/badge/skills/hassancs91/content-factory-starter/content-factory.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 | $0.00112 | $0.03715 |
| Opus 5 | $0.00056 | $0.01858 |
| Sonnet 5 | $0.00022 | $0.00743 |
| Haiku 4.5 | $0.00011 | $0.00371 |
Grade A, and why
Content Factory 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Factory — Orchestrator
This skill runs a content pipeline where the evidence is generated before the writing starts. The model is one component. The pipeline around it is what makes the output worth publishing.
Read SETUP.md once before the first run — the pipeline expects a handful of files to exist and a few decisions to have been made.
| Module | File | What it covers |
|---|---|---|
| Lab (cloud VMs, local Docker) | modules/lab.md | Where experiments run and how they get torn down |
| Recon | modules/recon.md | What to learn about the topic before writing |
| Assets | modules/assets.md | Captures, clones, charts, social cards |
| Verification | modules/verify.md | Loops V0–V6, the release gate |
| Knowledge base | modules/brain.md | Reading your voice in, writing lessons back |
| Writer profile | profiles/ | How a draft becomes a page on YOUR site |
The one rule that makes everything else work
content-lab/<slug>/PIECE.md is the single source of truth for a piece.
Update it after every meaningful step, not at session end. Any session must be able to
pick up any piece from PIECE.md alone: read LEDGER.md → read the piece's PIECE.md →
do what its next_action line says. Never rely on chat context surviving.
That rule is enforced rather than encouraged: LEDGER.md is rendered from the PIECE.md
files, so a piece whose frontmatter you let go stale disappears from the shared view. Only
one session may hold a piece, so PIECE.md has exactly one writer — which is why the ledger
can never be clobbered by a parallel session.
Load this before any task
- memory/MEMORY.md — the skill's own memory index. Load it FIRST,
before touching a piece, so past friction shapes what you do instead of being
rediscovered at cost. Then open any
memory/<file>.mdwhose description looks relevant. - Surface a one-line "Loaded N factory memories: …" so the owner knows what informed you.
What ships with it
41 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.
- lab/_config.py 2.5 KB runs code
- lab/auth.py 6.6 KB runs code
- lab/bootstrap-ubuntu.sh 937 B runs code
- lab/capture.py 4.9 KB runs code
- lab/clone-kit/chrome.css 3.6 KB
- lab/clone-kit/example-browser.html 605 B
- lab/clone-kit/example-terminal.html 879 B
- lab/dns.py 5.0 KB runs code
- lab/do.py 16 KB runs code
- lab/ledger.py 11 KB runs code
- lab/lint_draft.py 6.0 KB runs code
- lab/lock.py 16 KB runs code
- memory/lesson_assert_on_what_the_user_sees.md 1.9 KB
- memory/lesson_bash_s_stdin_trap.md 1.1 KB
- memory/lesson_evidence_scripts_pipefail_and_sentinels.md 2.5 KB
- memory/lesson_experiments_that_break_their_transport.md 2.8 KB
- memory/lesson_gpu_droplet_lab.md 1.8 KB
- memory/lesson_lab_cost_is_wallclock_not_experiments.md 2.1 KB
- memory/lesson_lazy_images_blank_in_fullpage_captures.md 1.3 KB
- memory/lesson_measure_before_you_reshoot.md 2.6 KB
- memory/lesson_never_edit_running_driver.md 1.2 KB
- memory/lesson_no_shared_mutable_files.md 4.2 KB
- memory/lesson_path_scoped_commit_ignores_the_index.md 2.5 KB
- memory/lesson_pkill_matches_the_remote_wrapper.md 1.5 KB
- memory/lesson_probe_differentiator_before_recon.md 2.1 KB
- memory/lesson_remote_script_traps.md 2.1 KB
- memory/lesson_timeboxed_experiments.md 1.7 KB
- memory/lesson_v6_capture_long_pages.md 1.8 KB
- memory/lesson_windows_experiment_harness.md 3.5 KB
- memory/MEMORY.md 5.4 KB
- modules/assets.md 4.1 KB
- modules/brain.md 5.0 KB
- modules/lab.md 6.9 KB
- modules/recon.md 4.2 KB
- modules/verify.md 5.4 KB
- profiles/writer-profile.example.md 4.1 KB
- SETUP.md 3.9 KB
- templates/claims.md 1.8 KB
- templates/evidence-manifest.md 2.4 KB
- templates/PIECE.md 5.4 KB
- templates/recon-report.md 1.8 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 · 240 lines · 112 tokens per session scan A 02c4237986aa
Content Factory is a skill published in the GitHub repository hassancs91/content-factory-starter (6 stars, last pushed 25d ago), licensed MIT. It adds 112 tokens to every session and 3,715 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
content-pipeline
Run a multi-agent content production pipeline where specialist agents work together to research, write, edit, optimise for SEO/GEO, and validate against analytics data — with a master agent reviewing all outputs before human approval. Use this skill whenever the user wants to produce content using multiple agents…
story-import
A tool for turning an existing novel into a structured writing project. It analyzes the book and organizes its characters, settings, plot plans, chapters, and tracking data for later writing.
story-long-analyze
A long-form fiction analysis workflow for breaking down a novel’s opening chapters, characters, pacing, turning points, relationships, and overall structure.
story-deslop
A writing editor for Chinese web novels that detects writing patterns often associated with AI-generated text and makes the prose feel more natural.
story-short-analyze
A Chinese-language guide for analysing short popular web fiction, such as stories published on 番茄, 故事会, or 知乎盐选. It examines the core premise, plot structure, emotional arc, twists, writing techniques, and reader appeal.
avoid-ai-writing
Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detect-only mode, an edit-in-place mode for files, an optional voice…