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 TenWalk/ieee-skills --skill ieee-methodsgit clone --depth 1 https://github.com/TenWalk/ieee-skillsWrote 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/tenwalk/ieee-skills/ieee-methods)<a href="https://agentmods.dev/skills/tenwalk/ieee-skills/ieee-methods"><img src="https://agentmods.dev/badge/skills/tenwalk/ieee-skills/ieee-methods/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/tenwalk/ieee-skills/ieee-methods"><img src="https://agentmods.dev/badge/skills/tenwalk/ieee-skills/ieee-methods.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00142 | $0.00890 |
| Opus 5.5 | $0.00057 | $0.00356 |
| Sonnet 5.5 | $0.00028 | $0.00178 |
| Haiku 4.5 | $0.00014 | $0.00089 |
Grade A, and why
ieee-methods 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 1mo 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IEEE Methods and Reproducibility
Use this skill to turn a method description into a reproducible IEEE communications methods block.
It sits between ieee-writing and ieee-experiments: writing explains the idea; this skill makes
the implementation, notation, and complexity auditable.
Core stance
- Reproducible beats impressive. A reviewer should be able to rebuild the main curve from the system model, parameter table, algorithm box, and solver/training details.
- Define every symbol at first use. If a variable appears in an equation, it needs a domain, dimension, unit when relevant, and role.
- Separate assumptions from simplifications. Assumptions define the studied regime; simplifications need a boundary or robustness check.
- Complexity claims need variables. State big-O in terms of antennas/users/subcarriers/RIS elements/iterations, not a vague "low complexity".
- No hidden implementation. Solver version, stopping tolerance, Monte-Carlo realization count, train/test split, and randomization policy are methods content, not footnotes.
When to open extra files
| File | Open when |
|---|---|
| references/reproducibility-checklist.md | Auditing or writing system/channel setup, simulation-parameter tables, randomization, solvers, training data, hardware/testbed/ray-tracing settings, or reproducibility statements |
| references/notation-and-complexity.md | Building notation tables, algorithm boxes, convergence statements, or big-O complexity analysis |
Use ieee-writing for full Section II/III prose, ieee-experiments for benchmark/metric design,
ieee-figure for result plots, and ieee-latex for IEEEtran formatting and compilation.
Workflow
- Identify the method object: system model, problem formulation, algorithm, analysis, neural network, simulation protocol, or testbed/ray-tracing setup.
- Extract the reproducibility variables: topology, channel, signal model, optimization variables, metrics, solver/training setup, and random quantities.
- Build a notation table for nontrivial papers: symbol, size/domain, meaning, first equation.
- Write the method in signal flow order: input -> transformation/channel/optimization -> output -> metric. Avoid listing modules without explaining information flow.
- Add a parameter table for experiments and shared settings. Put repeated constants there, not scattered through prose.
- For algorithms, add an algorithm box with initialization, loop, stopping criterion, and returned variables. Label exact, approximate, and learned steps.
- State convergence and complexity honestly: KKT/stationary/global only when proved; complexity per iteration plus total iteration count when applicable.
- Flag gaps that prevent reproduction rather than filling them by guess.
What ships with it
3 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.
- 1mo ago First seen · 67 lines · 142 tokens per session scan A 6ecfb37915a1
ieee-methods is a skill published in the GitHub repository TenWalk/ieee-skills (5 stars, last pushed 4mo ago), licensed MIT. It adds 142 tokens to every session and 890 once invoked, about $0.0006 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 2026-08-31.
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