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 agentmods add skills/docxology/template/citationnpx skills add docxology/template --skill citationgit 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/citation)<a href="https://agentmods.dev/skills/docxology/template/citation"><img src="https://agentmods.dev/badge/skills/docxology/template/citation.svg" alt="Measured on agentmods" 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 | $0.00142 | $0.00924 |
| Opus 5 | $0.00071 | $0.00462 |
| Sonnet 5 | $0.00028 | $0.00185 |
| Haiku 4.5 | $0.00014 | $0.00092 |
Grade A, and why
infrastructure-reference-citation 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 yesterday.
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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Submodule
BibTeX I/O matching projects/templates/template_code_project/manuscript/references.bib.
Reading
from infrastructure.reference.citation import parse_bibfile, parse_bibtex
db = parse_bibfile("projects/templates/template_code_project/manuscript/references.bib")
print(len(db)) # 8
print(db.keys()) # ['nocedal2006numerical', ...]
entry = db.find("boyd2004convex")
print(entry.entry_type) # 'article'
print(entry.get("author")) # 'Boyd, Stephen and Vandenberghe, Lieven'
print(db.preamble) # The @comment{...} block
Writing
from collections import OrderedDict
from infrastructure.reference.citation import (
BibEntry, BibDatabase, render_database, write_bibfile
)
db = BibDatabase()
db.add(BibEntry(
"article", "smith2024example",
OrderedDict([
("title", "An Example Paper"),
("author", "Smith, Alice and Jones, Bob"),
("journal", "Cambridge UP"),
("year", "2024"),
("pages", "1-10"), # auto-normalised to "1--10"
("doi", "10.1234/example"),
]),
))
print(render_database(db))
write_bibfile("output/refs.bib", db)
Convert from a search result
from infrastructure.reference.citation import paper_to_bibentry, generate_citation_key
from infrastructure.search.literature import Paper
paper = Paper(id="x", title="Adam", authors=["Kingma, Diederik P", "Ba, Jimmy"], year=2014, venue="ICLR", venue_type="conference")
entry = paper_to_bibentry(paper) # entry_type → "inproceedings", key → "kingma2014adam"
# Override either field:
entry = paper_to_bibentry(paper, citation_key="my_custom_key", entry_type="misc")
# Or generate a key without converting:
key = generate_citation_key(authors=["Cauchy, Augustin-Louis"], year=1847, title="Méthode générale")
# → "cauchy1847methode"
CLI
# Validate
uv run python -m infrastructure.reference.citation.cli validate refs.bib --strict
# Re-format in canonical layout
uv run python -m infrastructure.reference.citation.cli format refs.bib
# Convert literature-search JSON → BibTeX
uv run python -m infrastructure.reference.citation.cli convert papers.json refs.bib
What ships with it
10 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.
- yesterday First seen · 101 lines · 142 tokens per session scan A 89442960db56
infrastructure-reference-citation is a skill published in the GitHub repository docxology/template (19 stars, last pushed yesterday), licensed Apache-2.0. It adds 142 tokens to every session and 924 once invoked, about $0.0007 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.
Other skills, from other repositories
planning-with-files
Persistent file-based planning for multi-step AI-agent work. Keeps taskplan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and…
aviation-inspector
Use when a task needs the judgment of an Aviation Inspector — determining whether an air carrier's fleet is in compliance with an Airworthiness Directive across a maintenance-records sample, deciding where the FAA's compliance-and-enforcement ladder places a finding (compliance action vs. Letter of Correction vs.…
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-sciences-professor
Use when a task needs the judgment of a tenure-track or tenured Agricultural Sciences faculty member at a land-grant university — deciding whether to submit a grant this cycle versus wait, allocating time across the teaching/research/extension appointment split, diagnosing a stalled graduate student or field trial, or…
aircraft-mechanic
Use when a task needs the judgment of a certificated aircraft mechanic — triaging a maintenance discrepancy, deciding whether an item can be MEL-deferred or grounds the aircraft, working out an Airworthiness Directive's compliance deadline, reviewing a torque/safety-wire job before sign-off, or writing a…
animal-breeder
Use when a task needs the judgment of a livestock geneticist/animal breeder — selecting a sire against EPDs or genomic data, screening a proposed mating for inbreeding risk, deciding AI versus natural service, timing an estrus-synchronization protocol, or defending a breeding-goal tradeoff to a herd owner.