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/template-literature-meta-analysisWrote 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/template-literature-meta-analysis)<a href="https://agentmods.dev/skills/docxology/template/template-literature-meta-analysis"><img src="https://agentmods.dev/badge/skills/docxology/template/template-literature-meta-analysis/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/template-literature-meta-analysis"><img src="https://agentmods.dev/badge/skills/docxology/template/template-literature-meta-analysis.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 | $0.00039 | $0.00772 |
| Opus 5.5 | $0.00016 | $0.00309 |
| Sonnet 5.5 | $0.00008 | $0.00154 |
| Haiku 4.5 | $0.00004 | $0.00077 |
Grade A, and why
template-literature-meta-analysis 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 3d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
template-literature-meta-analysis
Project-scoped skill for the in-repo exemplar at
projects/templates/template_literature_meta_analysis/. Load this when working inside the project.
When to Use
- Working inside the
template_literature_meta_analysisexemplar — running scripts, editing source, or regenerating outputs. - Forking this exemplar as the starting scaffold for a new research project.
- Validating that the exemplar's contracts (thin-orchestrator, layer boundaries, no-mocks testing) still hold after changes.
Quick Reference
# From the repository root
# Canonical fresh-clone gate: provisions the project's isolated dependencies.
uv run python scripts/pipeline/stage_01_test.py --project templates/template_literature_meta_analysis --project-only
uv run python scripts/pipeline/stage_02_analysis.py --project templates/template_literature_meta_analysis
uv run python scripts/pipeline/stage_03_render.py --project templates/template_literature_meta_analysis
uv run python scripts/pipeline/stage_04_validate.py --project templates/template_literature_meta_analysis
uv run python scripts/pipeline/stage_05_copy.py --project templates/template_literature_meta_analysis
For an independent source checkout, first prepare its own environment with the
actual platform wheel matching this project's declared SDK pin and this project's dev extra as described in
STANDALONE.md. These candidates are unreleased;
do not assume they are available from a package index. Run from the standalone
checkout's root:
python -I -m pytest tests/ --cov=src --cov-fail-under=90
The standalone command uses its own pyproject.toml; it requires no Root-stage
script. The Stage-01 command above provisions dependencies for monorepo work.
Pitfalls
- Keep scripts thin. Business logic belongs in
src/or sharedinfrastructure/, not inscripts/. - No mocks. All tests must use real data, real files, and real computation.
- Select the documented command for the checkout. Use Stage 01 from the monorepo root, or the configured pytest command from the prepared standalone environment. Both require this exemplar's declared scientific dependencies.
- Outputs are disposable. Never hand-edit
output/— regenerate from source and config. - Use the correct working directory. Stage commands run from the monorepo root; standalone pytest runs from the exemplar root.
What ships with it
2 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.
- 3d ago Changed 77d5311755c1
- 11d ago Changed 204ceb1fe254
- 15d ago Changed · +13 lines f4daacb45ce6
- 1mo ago First seen · 63 lines · 39 tokens per session scan A 9a3806b606ab
template-literature-meta-analysis is a skill published in the GitHub repository docxology/template (20 stars, last pushed yesterday), licensed Apache-2.0. It adds 39 tokens to every session and 772 once invoked, about $0.0002 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.
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