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 | $0.00634 |
| Opus 5 | $0.00019 | $0.00317 |
| Sonnet 5 | $0.00008 | $0.00127 |
| Haiku 4.5 | $0.00004 | $0.00063 |
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 6d 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 — 63 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
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.
- Use the Stage-01 test command from the monorepo root. A direct root
pytestinvocation does not provision this exemplar's scientific dependencies. - Outputs are disposable. Never hand-edit
output/— regenerate from source and config. - Run from the repo root. Commands assume the template monorepo root
as working directory unless the child
AGENTS.mdstates otherwise.
Optional gap-filler search (Monid)
Use MCP connectors and configured retrieval keys first. For uncovered endpoints,
Monid (infrastructure/search/monid/) is infrastructure-only — pricing table:
PRICING.md. Offline
deep_research replay (scripts/08_deep_research_dispatch.py) remains the
exemplar's default long-form synthesis path.
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.
- 6d 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 (19 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 634 once invoked, about $0.0002 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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