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 skills add sweetcornna/mathodology --skill mathodology-project-orientationgit clone --depth 1 https://github.com/sweetcornna/mathodologyWrote 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/sweetcornna/mathodology/mathodology-project-orientation)<a href="https://agentmods.dev/skills/sweetcornna/mathodology/mathodology-project-orientation"><img src="https://agentmods.dev/badge/skills/sweetcornna/mathodology/mathodology-project-orientation/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/sweetcornna/mathodology/mathodology-project-orientation"><img src="https://agentmods.dev/badge/skills/sweetcornna/mathodology/mathodology-project-orientation.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 | $0.00022 | $0.00305 |
| Opus 5 | $0.00011 | $0.00152 |
| Sonnet 5 | $0.00004 | $0.00061 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
mathodology-project-orientation 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 2d 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.
What it actually says
Mathodology Repository Orientation
The maintained source is .claude/skills/, with roles in .claude/agents/,
workflow prompts in .claude/workflows/, and user documentation in docs/.
The root retains AGENTS.md, the two READMEs, LICENSE, .gitignore and .mcp.json.
Skill directories may include reference Markdown, attributed source snapshots, small licensed images, generated demonstration figures and optional scripts. A reference figure is teaching material, not contest evidence. Keep synthetic previews visibly labeled and reproducible. Do not add a dataset collection, application runtime, CI, package manifest or deployment framework.
.agents/skills/ is an ignored local mirror, never a second authoring source.
Before replacing this project's installed skills, back up its Mathodology
entries outside the checkout. Leave other skills and global directories alone.
.mcp.json is a client configuration for the keyless search MCP. It is retained;
custom user configurations and secrets do not belong in source control.
Contest output can live in ignored work/ or another working directory.
Historical application implementation is available through Git history.
For maintenance, optionally run the repository checker described in maintenance. The checker verifies metadata, references and boundaries; it does not assess mathematical quality.
What ships with it
1 file 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.
- 2d ago Changed · -54 lines · -10 tokens per session fe7afbaf748e
- 10d ago First seen · 84 lines · 32 tokens per session scan A 3e756daef86e
mathodology-project-orientation is a skill published in the GitHub repository sweetcornna/mathodology (202 stars, last pushed 3d ago), licensed MIT. It adds 22 tokens to every session and 305 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
rulesync
Generates and syncs AI rule configuration files (.cursorrules, CLAUDE.md, copilot-instructions.md) across 20+ coding tools from a single source. Use when syncing AI rules, running rulesync commands, importing or generating rule files, or managing shared AI coding configurations.
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.
autoprompt
Explicit-only useful-first orchestration. Invoke /autoprompt to turn a mission into one executable roadmap, build dependency-safe lanes, and verify the result with independent reviewers. Never infer invocation from ordinary requests. Never resume from leftover artifacts without an explicit resume instruction.
gitnexus
A code-graph analysis add-on for examining an existing codebase, including symbols, call paths, execution flows, and effects across repositories. It can query GitNexus through its command-line or MCP interfaces.
loop
Full execution protocol for MODE: LOOP — the compound-engineering loop: brainstorm → plan → build → review → improve, iterating under defense-in-depth stop conditions with generator/critic separation, durable resumable state, and mandatory compounding learning capture. Loaded on demand by the architect when the loop…