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/infrastructureWrote 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/infrastructure)<a href="https://agentmods.dev/skills/docxology/template/infrastructure"><img src="https://agentmods.dev/badge/skills/docxology/template/infrastructure/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/infrastructure"><img src="https://agentmods.dev/badge/skills/docxology/template/infrastructure.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 | $0.00080 | $0.02013 |
| Opus 5.5 | $0.00032 | $0.00805 |
| Sonnet 5.5 | $0.00016 | $0.00403 |
| Haiku 4.5 | $0.00008 | $0.00201 |
Grade A, and why
infrastructure-overview 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 7d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infrastructure Layer
The infrastructure/ package provides generic, reusable functionality for research projects. All business logic resides here (Layer 1) or in project-specific src/ (Layer 2). Scripts are thin orchestrators that coordinate these modules.
Finding skills (Cursor and other agents)
- Hub: This file lists every subpackage skill and a module map.
- Manifest:
.cursor/skill_manifest.jsonlists every discovered first-party skill (name,description,path); regenerate withuv run python -m infrastructure.skills write. - Search: default discovery covers
infrastructure/**/SKILL.md,scripts/**/SKILL.md, publicprojects/templates/**/SKILL.mdincluding.agents/skills, public resource-pool template skills underfonds/templates/,rules/templates/, andtools/templates/, plus.cursor/skills/. - In Cursor:
@infrastructure/SKILL.mdor@infrastructure/<module>/SKILL.mdto load context; pair with the matchingAGENTS.mdfor API tables. - Frontmatter: Each
SKILL.mdhas YAMLnameanddescriptionfor routing (see also the table ininfrastructure/README.md).
Module Map
| Module | Purpose | Key Imports |
|---|---|---|
autoresearch/ |
Deterministic research plans, stage-gate readiness, artifact/evidence reports | build_autoresearch_plan, validate_autoresearch_plan |
benchmark/ |
Deterministic benchmark manifests and public exemplar readiness scoring | run_benchmark_manifest, score_project_against_manifest |
config/ |
Repo defaults (.env.template, secure_config.yaml) |
(YAML/dotenv; use core.config_loader) |
core/ |
Logging, config, exceptions, pipeline, progress, retry, security | get_logger, load_config, PipelineExecutor |
docker/ |
Dockerfile, docker-compose.yml for container runs |
(CLI / docs/CLOUD_DEPLOY.md) |
validation/ |
PDF/Markdown/output validation, link checking, audits | validate_pdf_rendering, validate_markdown, verify_output_integrity |
rendering/ |
Multi-format output (PDF, HTML, slides) | RenderManager, RenderingConfig |
documentation/ |
Figure metadata, generated-file registries, source-derived glossary | FigureManager, publish_generated_figures, build_api_index |
llm/ |
Local LLM integration via Ollama | LLMClient, OllamaClientConfig, detect_repetition, check_format_compliance |
methods/ |
Methods orchestration plans over DAG, manuscript methods, artifacts, and evidence | build_methods_orchestration_plan, validate_methods_orchestration_plan |
orchestration/ |
Pipeline CLI, menu, project discovery, stage logging, secure-run wrapper (backs run.sh/secure_run.sh) |
build_parser, PipelineRunner, validate_project_slug, run_secure_pipeline |
publishing/ |
Academic publishing (DOI, citations, Zenodo, arXiv) | publish_to_zenodo, generate_citation_bibtex |
reference/ |
BibTeX I/O (read / write / convert) matching references.bib syntax |
parse_bibfile, render_database, paper_to_bibentry |
search/ |
Paperclip-style multi-source literature search (arXiv, Crossref, local, Paperclip) | LiteratureClient, SearchQuery, ArxivBackend, CrossrefBackend |
prose/ |
Prose analysis (readability, structure, editorial quality, manuscript reports) | analyze_manuscript, compute_metrics, analyze_structure, analyze_quality |
reporting/ |
Pipeline reports, error aggregation, dashboards | generate_pipeline_report, get_error_aggregator |
scientific/ |
Benchmarking, numerical stability, scientific templates | benchmark_function, check_numerical_stability |
sia/ |
SIA harness: task layout, fixture replay loop, evaluation runner | validate_task_dir, run_sia_loop, run_evaluation |
project/ |
Multi-project discovery and validation | discover_projects, validate_project_structure |
skills/ |
Enumerate and parse SKILL.md; maintain Cursor manifest |
discover_skills, write_skill_manifest |
steganography/ |
Cryptographic PDF watermarking and verification | SteganographyProcessor, SteganographyConfig, embed_steganography |
core/telemetry/ |
Unified pipeline telemetry (stage resources + diagnostics, JSON/text reports) | TelemetryCollector, TelemetryConfig |
What ships with it
60 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.
- __init__.py 3.7 KB runs code
- _version.py 552 B runs code
- .scope 4.0 KB
- AGENTS.md 4.6 KB
- autoresearch/__init__.py 3.8 KB runs code
- autoresearch/__main__.py 215 B runs code
- autoresearch/AGENTS.md 4.2 KB
- autoresearch/cli.py 6.4 KB runs code
- autoresearch/config.py 8.5 KB runs code
- autoresearch/metrics.py 3.2 KB runs code
- autoresearch/models.py 11 KB runs code
- autoresearch/orchestrator.py 8.4 KB runs code
- autoresearch/planner.py 3.1 KB runs code
- autoresearch/README.md 6.1 KB
- autoresearch/reports.py 7.4 KB runs code
- autoresearch/SKILL.md 2.5 KB
- autoresearch/validation_checks.py 23 KB runs code
- autoresearch/validation.py 6.1 KB runs code
- benchmark/__init__.py 1.1 KB runs code
- benchmark/__main__.py 156 B runs code
- benchmark/AGENTS.md 1.2 KB
- benchmark/README.md 2.3 KB
- benchmark/rubrics.py 2.8 KB runs code
- benchmark/SKILL.md 1.9 KB
- benchmark/template_harness.py 22 KB runs code
- benchmark/template_smoke_manifest.json 1.8 KB
- config/.env.template 1.6 KB
- config/acceptance-source-fixtures.json 28 KB
- config/AGENTS.md 812 B
- config/README.md 1.4 KB
- config/release-plan-contract.json 787 B
- config/root-case-policy.json 1.0 KB
- config/root-case-policy.part-0000.json 256 KB
- config/root-case-policy.part-0001.json 256 KB
- config/root-case-policy.part-0002.json 256 KB
- config/root-case-policy.part-0003.json 256 KB
- config/root-case-policy.part-0004.json 156 KB
- config/root-case-prerequisites.json 7.0 KB
- config/root-monid-discover-review.json 401 B
- config/secure_config.yaml 5.6 KB
- config/SKILL.md 1.3 KB
- core/__init__.py 1.7 KB runs code
- core/_bounded_kill.py 17 KB runs code
- core/_bounded_run_guardian.py 17 KB runs code
- core/_exceptions_core.py 7.7 KB runs code
- core/_exceptions_domains.py 2.8 KB runs code
- core/_optional_deps.py 577 B runs code
- core/_rate_limiting.py 6.9 KB runs code
- core/_validation.py 4.8 KB runs code
- core/agent_memory.py 6.5 KB runs code
- core/AGENTS.md 33 KB
- core/analysis_data_custody.py 8.3 KB runs code
- core/analysis_evidence.py 12 KB runs code
- core/analysis_figure_custody.py 10 KB runs code
- core/analysis_launch.py 11 KB runs code
- core/analysis_pipeline.py 11 KB runs code
- core/analysis_read_custody.py 9.1 KB runs code
- core/analysis_timeout.py 1.8 KB runs code
- core/analysis_write_custody.py 7.5 KB runs code
- core/bytecode_audit.py 15 KB runs code
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.
- 7d ago Changed 4f38523c2f5c
- 10d ago Changed 6961c166a19d
- 1mo ago First seen · 124 lines · 80 tokens per session scan A ab2008e45e19
infrastructure-overview is a skill published in the GitHub repository docxology/template (20 stars, last pushed 2d ago), licensed Apache-2.0. It adds 80 tokens to every session and 2,013 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.
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