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 AIScientists-Dev/Flowtrace --skill make-tracegit clone --depth 1 https://github.com/AIScientists-Dev/FlowtraceWrote 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/aiscientists-dev/flowtrace/make-trace)<a href="https://agentmods.dev/skills/aiscientists-dev/flowtrace/make-trace"><img src="https://agentmods.dev/badge/skills/aiscientists-dev/flowtrace/make-trace/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/aiscientists-dev/flowtrace/make-trace"><img src="https://agentmods.dev/badge/skills/aiscientists-dev/flowtrace/make-trace.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 3 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00076 | $0.03647 |
| Opus 5.5 | $0.00030 | $0.01459 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 (485 stars, last pushed 4mo ago), licensed MIT. It adds 76 tokens to every session and 3,647 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
fetch-url
Fetch a single URL and convert its content to Markdown. Use when you need to read a web page, documentation page, or API reference without indexing it. The content is returned as plain Markdown text on stdout.
firebase-messaging
Use when setting up Firebase Cloud Messaging, managing permissions and tokens, handling background/foreground notification taps, or dispatching messages server-side (HTTP v1).
firebase-cloud-functions
Use when calling callable functions (httpsCallable), passing data to server-side logic, handling function errors/timeouts, configuring regions, or testing with the Emulator Suite.
accessibility
Use when working on accessibility, a11y, WCAG, ARIA, screen readers, keyboard nav, focus order, contrast, alt text, captions, reduced motion, or target sizes; not language/culture/device (see inclusive-design).
karpathy-llm-wiki
Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.
excalidraw-architect
Choose and compose the right Excalidraw diagram - architecture, flowchart, sequence, state, ER, swimlane, process, timeline, quadrant, pyramid, venn, loop, gantt, bar, line, scatter, and more - using the excalidraw-architect-mcp server. Use whenever a reader would learn more from a picture than from prose, or when…