skills
AGENTS.md238 starsChanged 6 months agoMITView on GitHub
This repository is the raw ingredient pantry for Asgard AI Platform plugins: 263 coding agent skills organized by topic prefix. Every skill is a directory at the repo root, named {category}-{slug}, containing: Skills use topic-based prefixes (no skill- prefix). The 22 categories: 20 skills ship pure-stdlib Python scripts. Standards: When adding a new script: 1. Implement compute() with type-checked inputs 2. Implement verify() with at least 3 assertions covering happy path, edge case, and error case 3. Wire up main()…
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,700 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository315 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- algo-ad-biddingSkill
- algo-ad-budgetSkill
- algo-ad-ctrSkill
- algo-ad-gspSkill
- algo-ad-vcgSkill
- algo-blockchain-basicsSkill
- algo-blockchain-smart-contractSkill
- algo-ecom-bm25Skill
- algo-ecom-rankingSkill
- algo-ecom-searchSkill
- algo-forecast-arimaSkill
- algo-forecast-ensembleSkill
- algo-forecast-exponentialSkill
- algo-forecast-prophetSkill
- algo-hr-compensationSkill
- algo-hr-matchingSkill
- algo-hr-turnoverSkill
- algo-mfg-cpkSkill
- algo-mfg-doeSkill
- algo-mfg-fmeaSkill
- algo-mfg-spcSkill
- algo-net-centralitySkill
- algo-net-communitySkill
- algo-net-influenceSkill
- algo-nlp-ldaSkill
- algo-nlp-nerSkill
- algo-nlp-similaritySkill
- algo-nlp-summarizationSkill
- algo-price-bundleSkill
- algo-price-conjointSkill
- algo-price-dynamicSkill
- algo-price-elasticitySkill
- algo-price-van-westendorpSkill
- algo-rank-bayesianSkill
- algo-rank-eloSkill
- algo-rank-trueskillSkill
- algo-rank-wilsonSkill
- algo-rec-cfSkill
- algo-rec-contentSkill
- algo-rec-hybridSkill
- algo-rec-mfSkill
- algo-rec-sessionSkill
- algo-risk-altman-zSkill
- algo-risk-benfordSkill
- algo-risk-creditSkill
- algo-risk-varSkill
- algo-sc-bullwhipSkill
- algo-sc-eoqSkill
- algo-sc-newsvendorSkill
- algo-sc-routingSkill
- algo-sc-safety-stockSkill
- algo-seo-backlinkSkill
- algo-seo-contentSkill
- algo-seo-crawlSkill
- algo-seo-pagerankSkill
- algo-seo-schemaSkill
- algo-seo-technicalSkill
- algo-seo-tfidfSkill
- algo-social-engagementSkill
- The first 60 shown.
The file
We split this AGENTS.md into the rules it gives an agent
6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 13
Every skill is a directory at the repo root, named {category}-{slug}, containing:
- Distinctive: line 57
IRON LAW block: every skill must declare one non-obvious constraint
- Distinctive: line 82
When adding a new script:
- Very specific: line 86
Update the SKILL.md ## Scripts section with usage example
- Distinctive: line 90
When writing or modifying a skill, watch for:
- Very specific: line 103
Test scripts after editing: python <skill>/scripts/<script>.py --verify
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Asgard Skills — Repository Context
This repository is the raw ingredient pantry for Asgard AI Platform plugins: 263 coding agent skills organized by topic prefix.
Repository Purpose
- NOT a plugin: this repo holds raw skill files; plugins are assembled elsewhere by combining curated skills + MCPs
- NOT a template: see
skill-templatefor the plugin scaffolding - IS a versioned library of methodology + judgment + gotchas, packaged as Claude Agent Skills
Skill Anatomy
Every skill is a directory at the repo root, named {category}-{slug}, containing:
{category}-{slug}/
├── SKILL.md ← REQUIRED: frontmatter + methodology body
├── examples/ ← REQUIRED: directory must exist (uses .gitignore trick for empty dirs)
├── references/ ← REQUIRED: directory must exist; populated when SKILL.md offloads heavy content
└── scripts/ ← OPTIONAL: only present when the skill has executable scriptsNaming Convention
Skills use topic-based prefixes (no skill- prefix). The 22 categories:
grad- Graduate-level theoretical models
algo- Algorithms
biz- Business school frameworks
hum- Humanities / critical reasoning
tw- Taiwan-specific knowledge
ecom- E-commerce practical
econ- Economics fundamentals
meta- Interdisciplinary mental models
ops- Business operations
law- Legal frameworks
pr- PR & brand communications
cs- Customer service
data- Data analytics
mfg- Manufacturing
mkt- Digital marketing
med- Mass communication / journalism
soc- Social science
stat- Statistical methodology
tech- General tech (API, prompt eng, MCP)
ux- Design / UX methodology
fin- Finance practical
xborder- Cross-border commerceSKILL.md Rules
- Frontmatter (
name,descriptionrequired;metadataoptional) - Description: WHAT + WHEN, imperative tone, < 1024 chars, no XML angle brackets, includes trigger phrases
- Body: < 500 lines / < 5,000 tokens — offload heavy content to
references/ - IRON LAW block: every skill must declare one non-obvious constraint
- Output Format: a Markdown or JSON template the agent should follow
- Gotchas: 5-6 specific, actionable pitfalls (not generic advice)
- Skill name must not contain:
claudeoranthropic(reserved)
Design Patterns by Section
| Section | Primary patterns |
| Industry skills (ecom, mkt, mfg, ops, ...) | Phase-Gate, Hub-and-Spoke |
| Methodology (biz, hum, soc, econ, meta, law, ux, stat) | Concrete Verification, Iron Law |
| Graduate theory (grad-) | Hub-and-Spoke (HEAVY), assumptions as Iron Law |
| Algorithms (algo-) | Phase-Gate, Concrete Verification, complexity as Iron Law |
Scripts (Deterministic Calculators)
20 skills ship pure-stdlib Python scripts. Standards:
- Single file in
{skill}/scripts/ --help,--input <json>,--verify(self-test) flags- Outputs JSON to stdout
- Pure stdlib (no numpy/scipy/etc. unless documented)
- Errors as JSON to stderr
- Built-in
verify()function with assertions on known input/output pairs
When adding a new script:
- Implement
compute()with type-checked inputs - Implement
verify()with at least 3 assertions covering happy path, edge case, and error case - Wire up
main()withargparse - Update the SKILL.md
## Scriptssection with usage example
Quality Audit Anti-Patterns to Avoid
When writing or modifying a skill, watch for:
- Phantom Trigger — description over-matches (e.g., "everything is connected" triggers on any vague reference)
- Kitchen Sink — SKILL.md crammed with everything; should offload to
references/ - Over-Teaching — explaining basics the agent already knows (regression, p-values, prompt engineering)
- Missing Gotchas — generic advice instead of specific traps the agent would fall into
- Procedural Straitjacket — too rigid where judgment is needed; or too vague where precision matters
- Truism Iron Law — Iron Law that any competent agent would already follow ("be specific", "look at the data first")
- Non-verifiable Sample I/O — algo skills must have exact computable input → output, not approximate ranges
- Broken references/ pointers — SKILL.md references files that don't exist
Working in This Repo
- Test scripts after editing:
python <skill>/scripts/<script>.py --verify - Cross-skill references should use the new naming (no
skill-prefix) - The repository is published under MIT license; do not check in proprietary content
- See
TODO.mdfor current work in progress and pending items
See Also
skill-template— Plugin template repo- Asgard MCPs — Data-provider MCPs
- Claude Agent Skills documentation
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

