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/djscheuf/agentic-dev-ecosystem-template/design-story-implementationnpx skills add djscheuf/agentic-dev-ecosystem-template --skill design-story-implementationgit clone --depth 1 https://github.com/djscheuf/agentic-dev-ecosystem-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/djscheuf/agentic-dev-ecosystem-template/design-story-implementation)<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/design-story-implementation"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/design-story-implementation.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 5.1 | $0.00028 | $0.01103 |
| Opus 5 | $0.00014 | $0.00551 |
| Sonnet 5 | $0.00006 | $0.00221 |
| Haiku 4.5 | $0.00003 | $0.00110 |
Grade A, and why
design-story-implementation 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 6d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Steps:
1. Read the story analysis document
- Read the story analysis document provided by the user. This document contains the user story in a structured format, as well as some basic analysis of the upcoming functionality. The document will follow the schema defined in
/schema/analysis.schema.json.
2. Read the current reality audit file
- Read the current reality audit file provided by the user. This file contains the current application reality, as well as some basic analysis of the upcoming functionality.
3. Create the design document
- Create a design document in the same directory, as the provided analysis and audit json files, named
{story title}.design.json. - The design document will follow the schema defined in
/schema/design.schema.json.
4. Model the user's flow
Model the user's flow through the system as a sequence of domain events (not UI clicks). This shows how the story modifies the current reality workflow, focusing on "current reality + one step."
- Start from current reality workflow (existing persona flow)
- Identify workflow state transitions
- Model as sequence of domain events
- Show story's specific change from current state
Update the relevant section of the JSON
5. Define Instrumentation Events
Identify key events that should be instrumented for observability and monitoring. Use the VerbObjectContext or VerbObject naming pattern.
Update the relevant section of the JSON
6. Allocate Layer Responsibilities
Assign each AC element to the appropriate application layer(s) using responsibility heuristics. This is an iterative "catch ball" negotiation between layers, not strictly unidirectional.
Critical Principle: "Where is the information available to act?" - Responsibility emerges from where new information/behavior originates.
Layer Responsibility Heuristics: Frontend:
- Display (what user sees)
- Accessibility, colors, dialogue
- Sequence (occasionally)
- Security role differentiation/adaptation (NOT enforcement)
- Configuration based on user role
What ships with it
19 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.
- _tests/base.tests.yaml 6.8 KB
- _tests/data/add-user-badge.analysis.json 9.5 KB
- _tests/data/add-user-badge.audit.json 3.9 KB
- _tests/data/add-user-badge.zip 41 KB
- _tests/data/admin-tactic-types.analysis.json 12 KB
- _tests/data/admin-tactic-types.audit.json 4.4 KB
- _tests/data/admin-tactic-types.zip 42 KB
- _tests/data/improve-search-performance.analysis.json 6.5 KB
- _tests/data/improve-search-performance.audit.json 5.4 KB
- _tests/data/search-optimize.zip 71 KB
- _tests/designChecks.js 2.1 KB runs code
- _tests/prompt.md 263 B
- _tests/README.md 461 B
- _tests/test_cases.md 2.6 KB
- schema/design.example.json 2.7 KB
- schema/design.schema.json 14 KB
- schema/sentinel.schema.json 187 B
- schema/verify-params.schema.json 44 B
- verify.sh 8.0 KB runs code
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.
- 6d ago First seen · 125 lines · 28 tokens per session scan A d361ba76b181
design-story-implementation is a skill published in the GitHub repository djscheuf/agentic-dev-ecosystem-template (12 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 1,103 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.
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