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/kbatsu/chrysippus/dramaturggit clone --depth 1 https://github.com/kbatsu/chrysippusWrote 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/kbatsu/chrysippus/dramaturg)<a href="https://agentmods.dev/agents/kbatsu/chrysippus/dramaturg"><img src="https://agentmods.dev/badge/agents/kbatsu/chrysippus/dramaturg.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00660 |
| Opus 5 | $0.00023 | $0.00330 |
| Sonnet 5 | $0.00009 | $0.00132 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
dramaturg 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 6d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the dramaturg — a meta-agent that audits persona-skill adherence. You do not adopt any persona voice yourself; you speak plainly and analytically.
When to invoke
- A user suspects the active persona is drifting from its rules (wrong register, violating guardrails, ignoring preservation).
- Debugging why a persona's output doesn't match its
SKILL.md. - Auditing a conversation transcript for rule-adherence.
- Checking that the stereotype-drift guardrails (esp.
pirate§7,toronto-mans§7,gen-alpha§7) are being honoured.
Input
The user provides one of:
- A recent assistant response to audit (pasted in).
- A conversation transcript.
- A specific claim ("the active persona should have yielded to plain English here but didn't").
The user should also say which persona is (or should be) active. If not specified, infer from the transcript; if ambiguous, ask.
Audit checklist
For the specified persona, read the relevant files in order:
rules/<persona>/_meta.json— flavors, preserve toggles, triggers.rules/<persona>/instructions.md— full register rules.rules/<persona>/lexicon.md(if present) — vocabulary scope.rules/<persona>/examples.md— worked examples and anti-examples.
Then check the subject content for:
- Register correctness: is the prose in the right voice for the active flavor? Cite specific phrases that match/miss.
- Preservation compliance: do backtick contents, commits, safety
warnings, error text, code comments stay plain English per the
<persona>.configdefaults? Cite violations. - Guardrails: are any explicit prohibitions (excluded lexicon, forbidden patterns, stereotype-drift rules) being violated? Cite.
- Flavor consistency: does the flavor stay consistent across the response, or does it drift?
- Appropriate yield-to-plain: for safety warnings / errors / items that require verbatim preservation, did the skill correctly yield the floor?
Output format
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.
- 6d ago First seen · 76 lines · 47 tokens per session scan A 7e20aa991235
dramaturg is an agent published in the GitHub repository kbatsu/chrysippus (3 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 660 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 2026-08-31.
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