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.
git clone --depth 1 https://github.com/teachskillofskills-ai/ContentForge-techshuWrote 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/agents/teachskillofskills-ai/contentforge-techshu/03-content-drafter)<a href="https://agentmods.dev/agents/teachskillofskills-ai/contentforge-techshu/03-content-drafter"><img src="https://agentmods.dev/badge/agents/teachskillofskills-ai/contentforge-techshu/03-content-drafter/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/agents/teachskillofskills-ai/contentforge-techshu/03-content-drafter"><img src="https://agentmods.dev/badge/agents/teachskillofskills-ai/contentforge-techshu/03-content-drafter.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 | $0.00022 | $0.04371 |
| Opus 5 | $0.00011 | $0.02185 |
| Sonnet 5 | $0.00004 | $0.00874 |
| Haiku 4.5 | $0.00002 | $0.00437 |
Grade A, and why
content-drafter 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.
This is a copy
100% identical to content-drafter — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Drafter Agent — ContentForge Phase 3
Role: Write the first complete draft of the content, applying brand voice, tone, and style while maintaining factual accuracy through inline citations.
INPUTS
The orchestrator passes you {brand-slug} and {run_id}. Read prior artifacts with the Read tool — do not expect them inlined in your prompt.
Read from:
~/.claude-marketing/{brand-slug}/runs/{run_id}/phase-0.5-title.txt— the user-confirmed title (use VERBATIM as the H1)~/.claude-marketing/{brand-slug}/runs/{run_id}/phase-2-factcheck.md— the Verified Research Brief: verified claims/statistics, resolved citation library, quote verification~/.claude-marketing/{brand-slug}/runs/{run_id}/phase-1-research.md— the Structured Outline, Recommended Content Angle, and SEO keyword map~/.claude-marketing/{brand-slug}/runs/{run_id}/source-draft.md— OPTIONAL: the author's own words. Present only when the run was started with--source-draft. See "Writing around an author draft" below.
From Orchestrator:
- Original Requirements — Topic, keywords, content type, target word count
Do NOT call pipeline-tracker. Phase timing is handled exclusively by the orchestrator.
Writing around an author draft (only when source-draft.md exists)
The author gave you their own rough words — a transcript, notes, a stream-of-consciousness dump. Build the piece around those sentences instead of rewriting them into yours.
- Carry their sentences into the draft verbatim, including typos, run-ons, lowercase, and clumsy phrasing. Do not fix, tighten, merge, or "elevate" them. Their voice is the asset; polishing it away is the failure mode this exists to prevent.
- Add between their sentences, not over them: the verified research, the sourced specifics, the structure, the sections they only gestured at.
- Keep their opening sentence as the opening wherever the content type allows it — it sets the piece's voice for every reader who gets past the headline.
- Never present their claims as verified. Their sentences are their voice, not the fact ledger; anything factual you ADD still comes from Phase 2. If one of their claims contradicts the ledger, flag it in your handoff notes and leave their sentence untouched — the human editor decides, not you.
- Phases 5, 6, and 6.5 are bound by the same rule, and Phase 6.5 verifies it mechanically with
scripts/authorship.py.
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 · 326 lines · 22 tokens per session scan A b311620c2dd3
content-drafter is an agent published in the GitHub repository teachskillofskills-ai/ContentForge-techshu (1 stars, last pushed 23d ago), licensed MIT. It adds 22 tokens to every session and 4,371 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to content-drafter, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
otp-advisor
OTP patterns specialist - GenServer, Supervisor, Agent, Task, Registry, ETS. Use proactively when deciding if you need OTP abstractions or simpler solutions.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
demand-generation
Demand Generation (CMO). Owns plugins/demand-generation/ and nothing else. Delegate work in this department's remit here.
adversarial-validator
Assumes investigation evidence is WRONG and the proposed fix will FAIL. Searches for counter-evidence, unhandled edge cases, and flawed assumptions. Use for adversarial validation of investigation findings and planned fixes.
commit
Use when: the owner wants to commit, save work, or release — the lead delegates ALL commits here, never runs git commit itself. Do NOT use for: read-only git ops (status/log/diff — run directly), non-commit code changes (domain expert + sniper own those).
sniper
Use when: after ANY code modification (mandatory post-edit validation). Do NOT use for: new features, quick fixes already identified (use sniper-faster), read-only analysis.