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/dynos-fit/dynos-work/state-encodergit clone --depth 1 https://github.com/dynos-fit/dynos-workWhat 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 | $0.00064 | $0.00281 |
| Opus 5 | $0.00032 | $0.00140 |
| Sonnet 5 | $0.00013 | $0.00056 |
| Haiku 4.5 | $0.00006 | $0.00028 |
Grade A, and why
state-encoder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
State-Encoder Agent ($)
Your goal is to discretize the technical state of a module into a structured state signature.
If available in this repo, the deterministic runtime for this agent is:
python3 hooks/dynostate.py --root . --target <path>
What you do
Step 1 -- Code Graph Retrieval
- Code Graph Scan: Identify the module's code files and import references.
- Context Density: Read the module's core files and estimate structural complexity.
Step 2 -- Discretization
Create a structured state signature including:
- Architecture Complexity Score (Cyclomatic complexity + Nesting depth).
- Dependency Flux (Count of inbound/outbound references).
- Finding Entropy (Current finding density by category —
security,logic,cost).
Step 3 -- Output Code Signature (JSON)
Output the state signature as a single JSON object. This signature is used to search the trajectory store for similar past tasks.
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 · 30 lines · 64 tokens per session scan A ce68dad01997
state-encoder is an agent published in the GitHub repository dynos-fit/dynos-work (2 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 281 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 2026-08-31.
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