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 skills/aiscientists-dev/flowtrace/make-tracenpx skills add AIScientists-Dev/Flowtrace --skill make-tracegit clone --depth 1 https://github.com/AIScientists-Dev/FlowtraceWhat 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 | $0.00076 | $0.03647 |
| Opus 5 | $0.00038 | $0.01824 |
| Sonnet 5 | $0.00015 | $0.00729 |
| Haiku 4.5 | $0.00008 | $0.00365 |
Grade A, and why
make-trace 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Make Trace
You turn a source (anything that describes how a kind of task gets done) into a trace: a folder holding a DAG that a human and an AI both read while the work runs. This skill covers the whole path, from a blank folder to a finished run.
Before you start
Two reads give you the full surface. Do them once:
references/CLI.md(bundled next to this file) is the system contract: every command, thetrace.jsonschema, the reply payload schema, the path rules, the state machine.- The source itself. Read it closely; the steps you need are usually hiding in its prose. For a large or multi-file source, read the spine in full (the main document and any workflow section) and only sample the rest to confirm a step exists, rather than reading every file to the same depth.
The flowtrace binary drives everything. Get it in this order: honor $TRACE_BIN if it is set; else use it if it is on your PATH; else, inside a flowtrace checkout, use the build under target/ (target/release/flowtrace, else target/debug/flowtrace) or build one with ./scripts/install.sh from the repo root; else clone the repo first (git clone https://github.com/AIScientists-Dev/Flowtrace.git) and run its ./scripts/install.sh. Building needs Node and Rust and takes a few minutes the first time — it builds the web UI and the CLI and symlinks flowtrace to ~/.local/bin. When you forget a shape mid-task, the binary self-documents: flowtrace <cmd> --help, and flowtrace explain <type> (e.g. flowtrace explain trace, flowtrace explain reply).
The cycle
1. Scaffold
cd <wherever you keep traces> # conventionally ~/traces/
flowtrace init <slug> # creates <slug>/ with .git and an empty trace.json
flowtrace init makes a subfolder named <slug> under the current directory, not in place.
2. Lift the source into a DAG (the hard part)
Read the source and pull out the steps hiding in it. Fill trace.json#steps, and for each step set from_steps, its upstream dependencies. The DAG is the whole point: decide what runs in parallel and what fans in.
What ships with it
1 file 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.
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 · 191 lines · 76 tokens per session scan A 82cf0bdf0eb1
make-trace is a skill published in the GitHub repository AIScientists-Dev/Flowtrace (488 stars, last pushed 2mo ago), licensed MIT. It adds 76 tokens to every session and 3,647 once invoked, about $0.0004 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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