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.
git clone --depth 1 https://github.com/Oriolshhh/runware-image-mcpWrote 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/rules/oriolshhh/runware-image-mcp/spec-engineering)<a href="https://agentmods.dev/rules/oriolshhh/runware-image-mcp/spec-engineering"><img src="https://agentmods.dev/badge/rules/oriolshhh/runware-image-mcp/spec-engineering/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/rules/oriolshhh/runware-image-mcp/spec-engineering"><img src="https://agentmods.dev/badge/rules/oriolshhh/runware-image-mcp/spec-engineering.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 | $0.00007 | $0.00624 |
| Opus 5.5 | $0.00003 | $0.00250 |
| Sonnet 5.5 | $0.00001 | $0.00125 |
| Haiku 4.5 | $0.00001 | $0.00062 |
Grade A, and why
spec-engineering 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: spec-engineering
Spec Engineering
Purpose
Convert a request into a precise, testable specification that a reviewer can approve and an implementer can follow without guessing.
When to use it
- Any non-trivial change, new feature, or behavior change.
- When requirements are ambiguous or stakeholders disagree.
Instructions
- Read fresh repository context and relevant source before asking questions.
- Ask one batch of at most three decision-changing questions (five only when unavoidable); state safe defaults for non-blocking ambiguity.
- Choose
direct-spec,specialist-assisted-spec, orfull-council-specfrom complexity, reversibility, cross-cutting scope, security, and product risk. - For specialist-assisted planning, select only relevant reviewers and gather
separate evidence-backed reports, parallelizing only with native isolated
agents. Use
/councilfor the full-council path. - Capture background, user stories, explicit non-goals, assumptions, and any meaningful specialist disagreement.
- Write numbered, testable requirements and map tests to each requirement.
- Describe data/API changes, UI/UX states, compatibility, rollout, and edge cases.
- Break work into dependency-aware tasks. Each task names its owner role, requirement IDs, dependencies, ownership area, acceptance criteria, tests, parallelizability, and integration point.
- Save to
.agent/specs/<kebab-case-name>.mdand request approval. - Include the
/specfrontmatter contract and keep status/revision metadata synchronized when the document changes.
Output format
A single Markdown spec with: title, goal, background, user stories, requirements, non-goals, UI/UX notes, data and API changes, edge cases, test plan, planning path and consultations, implementation tasks, review checklist, open questions.
Anti-patterns
- Vague requirements that cannot be verified.
- Silent assumptions instead of explicit open questions.
- Asking the user for information available in repository context.
- Invoking every specialist regardless of relevance.
- Calling simulated role passes independent subagents.
- Marking tasks parallelizable despite shared files or unresolved dependencies.
- Starting implementation before approval.
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 · 64 lines · 7 tokens per session scan A 7115b9ba54b1
spec-engineering is a cursor rule published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 7 tokens to every session and 624 once invoked, about $0.0000 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 2026-09-03.
Other cursor rules, from other repositories
fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.
pre-flight-check
Mandatory fail-fast quality gate — run Typecheck, Lint, Test, and Security Audit sequentially before declaring any task done or committing code.