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 djscheuf/agentic-dev-ecosystem-template --skill analyze-storygit 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/analyze-story)<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/analyze-story"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/analyze-story.svg" alt="Measured on agentmods" 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 | $0.00053 | $0.00896 |
| Opus 5 | $0.00026 | $0.00448 |
| Sonnet 5 | $0.00011 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
analyze-story 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Steps:
1. Read the Extracted Intent
- Read the extracted intent json document.
2. Read the provided document
- read the conents of the raw_prompt field in the extracted intent json document, either the file under the provided path or the verbatim text.
2. Create Analysis JSON File
- create a new json file in the same directory as the extracted intent json document, using the same filename but with the suffix
.analysis.json. e.g. "create-object-with-validation.analysis.json" - The json will follow
/schema/analysis.schema.json. - set the raw_request to the file path, relative to repo root, of the provided document, or to the verbatim text provided if no document was sent.
3. Analyze the Capability
Break down what's being requested:
CAPABILITY ANALYSIS:
├── Core action: [The main thing user does]
├── Inputs required: [What data is needed?]
├── Outputs expected: [What should result?]
├── State changes: [What data is modified?]
└── Side effects: [Notifications, logs, etc.]
Map to system components:
├── UI affected: [Screens, forms, buttons]
├── API endpoints: [New or modified]
├── Database changes: [Schema, queries]
└── External services: [Third-party integrations]
Fill in the appropriate section of the JSON.
4. Examine Acceptance Criteria
For each acceptance criterion:
- review the extracted crietion
- confirm testability, re-write scenario if not testable
- identify dependencies, that is other criteria this relates to
Ensure we have acceprtrance criteria for happy path, error handling, boundary conditions, and permission/access scenarios. Generate them if missing.
5. Identify Edge Case
Systematically consider:
INPUT EDGE CASES:
□ Empty/null values
□ Maximum length inputs
□ Special characters (unicode, emojis)
□ Invalid formats
□ Boundary values
STATE EDGE CASES:
□ First-time use (no existing data)
□ Maximum data limits
□ Concurrent modifications
□ Partial completion states
USER EDGE CASES:
□ No permissions
□ Expired sessions
□ Multiple devices
□ Interrupted workflows
SYSTEM EDGE CASES:
□ External service unavailable
□ Network timeout
□ Database errors
□ Rate limiting
And capture criteria for each edge case under edge_cases section.
What ships with it
14 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/_data/administer-tactic-types-and-delivery-methods.intent.json 6.6 KB
- _tests/_data/create-tactic-with-validation.intent.json 3.3 KB
- _tests/_data/display_name_story.intent.json 3.0 KB
- _tests/_data/example-story.intent.json 2.3 KB
- _tests/_data/improve-search-performance.intent.json 3.0 KB
- _tests/base.tests.yaml 2.5 KB
- _tests/partial_slice.tests.yaml 2.9 KB
- _tests/prompt.md 131 B
- _tests/test_cases.md 1.3 KB
- schema/analysis.example.json 4.4 KB
- schema/analysis.schema.json 21 KB
- schema/sentinel.schema.json 187 B
- schema/verify-params.schema.json 49 B
- verify.sh 10 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.
- 8d ago First seen · 115 lines · 53 tokens per session scan A 197c37808a0b
analyze-story is a skill published in the GitHub repository djscheuf/agentic-dev-ecosystem-template (12 stars, last pushed 2d ago), licensed MIT. It adds 53 tokens to every session and 896 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 2026-08-30.
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