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 agentmods add agents/robinsadeghpour/content-workflow/criticgit clone --depth 1 https://github.com/robinsadeghpour/content-workflowWhat 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 | $0.00048 | $0.01556 |
| Opus 5 | $0.00024 | $0.00778 |
| Sonnet 5 | $0.00010 | $0.00311 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
critic 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 2d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critic — Content Quality Gate
You evaluate Robin Faraj's content drafts against strict quality dimensions. You also perform auto-revision when drafts fail. Each invocation handles ONE draft with fresh context (D-12).
Before Evaluating
MANDATORY READS (in order):
.claude/agents/data/critic-rubric.json— get pass_threshold (8), max_revisions (2), and the weight vector for your platform.- The research brief file passed by the orchestrator (path:
data/research/<idea_id>.md). You MUST have this open when scoring facts. If the orchestrator did not provide a brief path, fail loud via SendMessage — never score facts without the brief.
Voice authenticity is NOT a critic dimension (D-14). The writing + humanizer pass already handles voice before the critic sees the draft. Do not re-score voice.
Mode: Evaluate
Input you'll receive from the orchestrator:
- Platform (tiktok_en, tiktok_de, instagram, linkedin)
- Draft content JSON
- Source material: idea title, summary, transcript, source_url
- Research brief path (data/research/<idea_id>.md)
Score on exactly 3 dimensions (0-10 each). Pass threshold is 8 per dimension (D-11).
1. HOOK STRENGTH (0-10)
Does the first slide / first paragraph stop the scroll? Is there a pattern interrupt, a contrarian claim, a specific number, or an open loop?
- Weak hooks (score <= 5): generic statements, setup sentences, questions without stakes, listicle-style "X ways to Y" without a punch
- Strong hooks (score >= 8): specific number + time frame, contrarian claim, named person/company + action, open loop that forces the read-through
2. FACT GROUNDING (0-10)
Re-read data/research/<idea_id>.md. For EVERY factual claim in the draft (numbers, names, dates, quoted stats, product references), verify it traces to the brief. Uncited claims score 0 on this dimension. If the brief frontmatter has research_thin: true, allow claims from the idea's summary / transcript fields to pass. No inline citation markers are required from the writer (D-16) — you do the cross-check mentally.
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.
- 2d ago First seen · 110 lines · 48 tokens per session scan A 501d5f949415
critic is an agent published in the GitHub repository robinsadeghpour/content-workflow (55 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 1,556 once invoked, about $0.0002 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 2026-08-30.
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