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/docxology/templatenpx agentmods add skills/docxology/template/provenanceWrote 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/docxology/template/provenance)<a href="https://agentmods.dev/skills/docxology/template/provenance"><img src="https://agentmods.dev/badge/skills/docxology/template/provenance/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/docxology/template/provenance"><img src="https://agentmods.dev/badge/skills/docxology/template/provenance.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 | $0.00103 | $0.01144 |
| Opus 5.5 | $0.00041 | $0.00458 |
| Sonnet 5.5 | $0.00021 | $0.00229 |
| Haiku 4.5 | $0.00010 | $0.00114 |
Grade A, and why
provenance-dag 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Provenance DAG
Content-addressed provenance DAG for tracking research artifact lineage. Every artifact node is identified by a SHA-256 content hash; edges record which pipeline stage produced each artifact from which inputs.
Quick Start
from infrastructure.provenance import ArtifactNode, EdgeRelation, Provenance, RunNode
store = Provenance.with_path("output/.provenance")
# Record that a run produced an artifact
run = RunNode.create("analysis run", command="uv run python scripts/pipeline/stage_02_analysis.py")
artifact = ArtifactNode.create("results.json", path="output/results.json")
store.record(run)
store.record(artifact)
# Link the artifact to the run that produced it
store.link(run.node_id, artifact.node_id, EdgeRelation.produced_by)
CLI
# Record an artifact node
uv run python -m infrastructure.provenance record-artifact "results.json" --path output/results.json
# List all recorded nodes (optionally filter by kind: artifact/run/source/claim)
uv run python -m infrastructure.provenance list --kind artifact
# Run the DAG-wide review pass (missing hashes, missing exit codes, etc.)
uv run python -m infrastructure.provenance review --json
# Run the DAG graph structural and acyclicity validation
uv run python -m infrastructure.provenance validate --json
There is no link or query CLI subcommand — those are library-only
(Provenance.link() / Provenance.query()); the CLI exposes
list, record-artifact, review, and validate.
Pipeline Orchestrator
# Record provenance for a named project and pipeline stage
uv run python scripts/pipeline/stage_09_provenance_record.py --project my_project --stage analysis
# Record with explicit input/output glob patterns and a custom store path
uv run python scripts/pipeline/stage_09_provenance_record.py \
--project my_project \
--stage render \
--outputs "output/*.pdf" \
--store-path output/.provenance/dag.json
There is no projects/{name}/manuscript/config.yaml provenance: block —
config-driven provenance is not implemented; every run is parameterized via
CLI flags on the stage script above.
What ships with it
11 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.
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 · 138 lines · 103 tokens per session scan A 2e0689645318
provenance-dag is a skill published in the GitHub repository docxology/template (20 stars, last pushed today), licensed Apache-2.0. It adds 103 tokens to every session and 1,144 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
aerospace-engineering-technician
Use when a task needs the judgment of an Aerospace Engineering and Operations Technologist/Technician — verifying an installed fastener's preload against a drawing's torque callout via the T=K·D·F relationship, reducing strain-gauge data from a structural proof-load test into stress and checking it against an…
agricultural-engineer
Use when a task needs the judgment of an agricultural engineer — sizing a center-pivot or drip irrigation system's peak capacity against crop water demand, computing lateral grain-bin wall pressure with Janssen's equation, sizing a waterway or tile-drainage system with Manning's equation and an NRCS design-storm…
automotive-engineering-technician
Use when a task needs the judgment of an Automotive Engineering Technician — setting up and instrumenting test equipment (strain-gauge bridges, thermocouples, load/torque sensors) to an engineer's written test plan, selecting DAQ sample rate and an SAE J211 CFC filter class for a vehicle test channel, verifying…
calibration-technician
Use when a task needs the judgment of a Calibration Technologist/Technician — computing a Test Uncertainty Ratio (TUR) and deciding whether it meets the 4:1 target, building a measurement uncertainty budget (Type A/Type B, GUM-style) for a calibration, tracing a reference standard's chain of custody to NIST/SI…
acoustical-engineer
Use when a task needs the judgment of an Acoustical Engineer — calculating room reverberation time (RT60) and specifying absorption/reflection treatment for a space, evaluating a wall or floor assembly's STC/IIC rating against a code or design target, diagnosing why a completed space fails its acoustic design intent…
agricultural-inspector
Use when a task needs the judgment of an Agricultural Inspector — grading a lot of produce against a USDA grade standard's defect tolerances, evaluating agricultural water test results against FSMA microbial thresholds, checking a pesticide residue result against the commodity-specific EPA tolerance, deciding whether…