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 docxology/template --skill reproducibilitygit clone --depth 1 https://github.com/docxology/templateWrote 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/reproducibility)<a href="https://agentmods.dev/skills/docxology/template/reproducibility"><img src="https://agentmods.dev/badge/skills/docxology/template/reproducibility/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/reproducibility"><img src="https://agentmods.dev/badge/skills/docxology/template/reproducibility.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00027 | $0.00306 |
| Opus 5 | $0.00014 | $0.00153 |
| Sonnet 5 | $0.00005 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
Reproducibility Workflow-Graph Assessment 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 5d 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
Instructions
You are interacting with the src/reproducibility/ module. This decomposes a paper's own described pipeline (source/method/experiment/sink steps) into a workflow graph and scores how reproducible that pipeline is from the paper's own text.
Agentic Interface (MCP Strategy)
- Config-Driven Orchestration: Never hardcode LLM parameters or scoring weights (
ContentWeights,StructuralWeights) within Python scripts. Bind them toLLMConfigand thereproducibility_assessmentblock ofconfig.yaml, loaded viaconfig_loader.load_reproducibility_config(). - Evidence-Backed Nodes Only: Every
WorkflowNodemust carry a non-emptysource_quotecopied verbatim from the paper's full text. Never accept or fabricate a node without one — this is the node's entire evidentiary basis. - Fulltext Gating: This module only extracts from full text on disk, never from title/abstract alone. When
project_config.fulltext.enabledis false and no--fulltext-diroverride is supplied, treat areproducibility_assessmentrun as a no-op that still yields valid, empty-but-well-formed outputs — never mistake the warning for a crash.
What ships with it
8 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.
- 5d ago First seen · 15 lines · 27 tokens per session scan A b34b41c79869
Reproducibility Workflow-Graph Assessment is a skill published in the GitHub repository docxology/template (19 stars, last pushed today), licensed Apache-2.0. It adds 27 tokens to every session and 306 once invoked, about $0.0001 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 2026-09-03.
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