Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/dynos-fit/dynos-worknpx agentmods add skills/dynos-fit/dynos-work/trajectoryWrote 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/dynos-fit/dynos-work/trajectory)<a href="https://agentmods.dev/skills/dynos-fit/dynos-work/trajectory"><img src="https://agentmods.dev/badge/skills/dynos-fit/dynos-work/trajectory.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 | $0.00049 | $0.00519 |
| Opus 5 | $0.00024 | $0.00260 |
| Sonnet 5 | $0.00010 | $0.00104 |
| Haiku 4.5 | $0.00005 | $0.00052 |
Grade A, and why
trajectory 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 yesterday.
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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dynos-work: Trajectory (Sequence Memory)
This is the memory layer for prior task traces. It is retrieval support, not an autonomous policy engine.
Ruthlessness Standard
- Retrieved history is evidence of recurrence, not permission to cargo-cult old solutions.
- If current code contradicts memory, trust the repo and call the memory mismatch out.
- Do not store or retrieve traces so loosely that they become decorative noise.
If available in this repo, the deterministic runtime for this skill is:
python3 hooks/trajectory.py rebuild --root .
python3 hooks/trajectory.py search query.json --root . --limit 3
What you do
Step 1 -- Task Trace Extraction (PUSH)
Immediately after a successful task completion and /dynos-work:learn:
- Trace Reconstruction: Reconstruct the sequence of (State, Action, Reward) for the entire task.
- Update Registry: Push the sequence into the versioned store at
.dynos/trajectories.json. - Outcome Summary: Record enough metadata to help future retrieval find similar successful tasks.
Step 2 -- Behavioral Retrieval (PULL)
During the "Founder Phase" or "Planning Phase":
- State Signature Search: Call the
state-encoderto get the current module's state signature ($). - Trajectory Search: Use the deterministic similarity search in
hooks/trajectory.pyto find the 3 most similar successful trajectories intrajectories.json.
Step 3 -- Advisory Use
When a similar prior task is found:
- Use it to surface likely failure modes, test gaps, and architecture risks.
- Never copy its implementation plan or decision path blindly.
- If current repo evidence conflicts with retrieved history, trust current repo evidence.
Hard Rules
- Trajectory Integrity: Never modify a past trajectory; they are immutable ground truth.
- Anonymization: Strip all local paths and IDs from the trajectories before they are indexed for search.
- Advisory Only: Retrieval may influence prioritization, but it never overrides hard validation or human approval.
- Schema First: Trajectories must be written in the versioned store format. Do not append ad hoc JSON blobs.
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.
- yesterday First seen · 47 lines · 49 tokens per session scan A e5efc5ce8382
trajectory is a skill published in the GitHub repository dynos-fit/dynos-work (2 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 519 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 2026-09-07.
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