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 linkpranay-ai/context-engineering-protocol --skill demo-write-user-storiesgit clone --depth 1 https://github.com/linkpranay-ai/context-engineering-protocolWrote 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/linkpranay-ai/context-engineering-protocol/demo-write-user-stories)<a href="https://agentmods.dev/skills/linkpranay-ai/context-engineering-protocol/demo-write-user-stories"><img src="https://agentmods.dev/badge/skills/linkpranay-ai/context-engineering-protocol/demo-write-user-stories/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/linkpranay-ai/context-engineering-protocol/demo-write-user-stories"><img src="https://agentmods.dev/badge/skills/linkpranay-ai/context-engineering-protocol/demo-write-user-stories.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 | $0.00064 | $0.01807 |
| Opus 5 | $0.00032 | $0.00903 |
| Sonnet 5 | $0.00013 | $0.00361 |
| Haiku 4.5 | $0.00006 | $0.00181 |
Grade A, and why
demo-write-user-stories 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 8d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Demo: Writing User Stories (worked example)
Overview
This is a lean, from-scratch reference implementation of a real downstream
consumer of CEP context packages — not a toy, and not part of core CEP.
Given a feature description, it writes standard-form user stories, grounded
in an approved context package's context_items when one is available, and
follows the same discover/load/tag/reverse-index loop every consuming skill
in this repo follows via CONSUMING-CONTEXT-PACKAGE.md.
It is deliberately minimal: no actor taxonomy, no Enabler/NFR/ Requirement-Note story types, no org-convention lookup, no scoring rubric. Any team that wants a production backlog tool should build one of those on top of this pattern — this skill exists to show the pattern itself, cleanly, end to end, and to be genuinely usable as-is for a quick, honestly-grounded first pass at a feature's user stories.
Scope note: this skill writes functional user stories only — plain "As a / I want / so that" statements. It does not distinguish Enabler stories, non-functional requirements, or requirement notes from functional stories; a production backlog tool should make that distinction, a lean reference example does not need to.
Inputs
- Feature description (required) — one or two sentences describing the feature or behavior to write stories for, the way a developer would actually phrase a ticket.
- Context package path (optional) — an explicit path to an approved
contexts/<id>.yamlfile to use instead of discovering one. If given, skip step 1's glob check below and treat that file as the "Found" package for step 2 onward, subject to the same existence/approval check (non-emptyapproved_by).
Steps
- Discover or load a context package — follow
.github/skills/ult-context-generate/CONSUMING-CONTEXT-PACKAGE.mdsteps 0–3, using the feature description as the input artifact for step 0's tag scan (it will usually carry no[Context: ...]tag for a bare ask — that's expected, fall through to step 1's glob check) and an explicit package path (if given) per "Inputs" above. Loadcontext_items,decisions_log/decisions,aspects, andsummaryper step 3 if a package is found and approved.
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.
- 8d ago First seen · 170 lines · 64 tokens per session scan A db95ce7a3425
demo-write-user-stories is a skill published in the GitHub repository linkpranay-ai/context-engineering-protocol (8 stars, last pushed yesterday), licensed Apache-2.0. It adds 64 tokens to every session and 1,807 once invoked, about $0.0003 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 2026-08-31.
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