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 aemrebarut/herdr-dagr --skill dagr-producergit clone --depth 1 https://github.com/aemrebarut/herdr-dagrWrote 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/aemrebarut/herdr-dagr/dagr-producer)<a href="https://agentmods.dev/skills/aemrebarut/herdr-dagr/dagr-producer"><img src="https://agentmods.dev/badge/skills/aemrebarut/herdr-dagr/dagr-producer/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/aemrebarut/herdr-dagr/dagr-producer"><img src="https://agentmods.dev/badge/skills/aemrebarut/herdr-dagr/dagr-producer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00070 | $0.06116 |
| Opus 5 | $0.00035 | $0.03058 |
| Sonnet 5 | $0.00014 | $0.01223 |
| Haiku 4.5 | $0.00007 | $0.00612 |
Grade A, and why
dagr-producer 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 13d 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 — 499 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dagr producer — write the run, prove the run
You are the producer: the single writer of a run file that dagr view
renders live. dagr is a representation kernel: you assert task truth, and
it derives only defined view signals from those facts. Missing or wrong facts
still produce a missing or wrong graph; there is no workflow engine to repair it.
Contract version: "dagr": 3 (v1/v2 files remain readable; write v3 for new runs).
Find your validator (before you write anything)
The check loop below is the only feedback you get, so resolve the dagr
binary FIRST and stop if you can't:
$DAGR_BINif set;command -v dagr(on PATH);- the plugin/repo build:
<dagr repo>/target/release/dagr— inside a herdr pane the runtime injects$HERDR_PLUGIN_ROOT, which IS the dagr repo root; - fallback:
cargo run --manifest-path <dagr repo>/Cargo.toml -- check ….
No validator available → do not start writing run files; say so and stop. An unvalidated run file is exactly the silent wrongness this whole system exists to prevent.
The loop (non-negotiable)
write run.json.tmp → dagr check run.json.tmp --strict --json → fix → repeat until []
→ THEN rename over run.json
Validate the candidate, then publish it — never the other way around.
The pane renders whatever run.json holds, immediately; renaming an
invalid candidate over it shows your error state to every viewer while
you iterate. The safe transaction:
- Write the complete next document to
run.json.tmp(same directory — rename must be atomic, so same filesystem). dagr check run.json.tmp --strict --json. Exit 0 with[]is clean; exit 1 means findings (E-codes are errors; W-codes mean representable- but-suspect — fix them unless you can say why not;--stricttreats them as failures, prefer it). Exit 2 means the validator could not read the file at all — a path or tooling problem, never a document problem; stdout is empty on that path, so never treat empty output as clean. Stop, re-run the preflight, and never publish on a non-zero exit.- Only when clean:
mv run.json.tmp run.json(atomic rename — the pane reloads on mtime and never sees a half-written or invalid file). - On failure: fix the temp file and re-check. The previous live file
stays untouched — never leave
run.jsonitself in an error state.
What ships with it
9 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.
- examples/01-init.json 196 B
- examples/02-first-attempt.json 784 B
- examples/03-send-back.json 2.3 KB
- examples/04-gate-promotion.json 2.3 KB
- examples/05a-policy-declared.json 1.3 KB
- examples/05b-policy-materialized.json 1.9 KB
- examples/06-evidence-tiers.json 3.3 KB
- examples/07-answer-question.json 1.7 KB
- examples/08-project-scopes-and-message.json 1.9 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.
- 13d ago First seen · 499 lines · 70 tokens per session scan A b8c306e349e2
dagr-producer is a skill published in the GitHub repository aemrebarut/herdr-dagr (73 stars, last pushed 20d ago), licensed Apache-2.0. It adds 70 tokens to every session and 6,116 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 2026-08-30.
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