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/commands/oriolshhh/runware-image-mcp/spec-detailed)<a href="https://agentmods.dev/commands/oriolshhh/runware-image-mcp/spec-detailed"><img src="https://agentmods.dev/badge/commands/oriolshhh/runware-image-mcp/spec-detailed/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/commands/oriolshhh/runware-image-mcp/spec-detailed"><img src="https://agentmods.dev/badge/commands/oriolshhh/runware-image-mcp/spec-detailed.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 | $0.00022 | $0.01146 |
| Opus 5 | $0.00011 | $0.00573 |
| Sonnet 5 | $0.00004 | $0.00229 |
| Haiku 4.5 | $0.00002 | $0.00115 |
Grade A, and why
spec-detailed 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 9d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/spec-detailed — Create a detailed spec with deeper questioning
Purpose
Produce a more exhaustive, less assumption-heavy specification when the user wants the agent to ask more questions and pin down exactly what should be built.
Use this when precision matters more than speed: product flows, UX details, security-sensitive behavior, migrations, billing, permissions, API contracts, or anything where a wrong default would be expensive.
Invocation
/spec-detailed <description of the work>
Accepted input
A request, problem statement, ticket, mockup, screenshot, user story, or rough idea, with any known constraints and desired level of strictness.
Prerequisites
A HarnessKit workspace (harnesskit init). No approved spec required.
Procedure
- Read
.agent/context/README.mdand routing when present. Inspect task-relevant source, existing specs, tests, UI routes, APIs, schemas, and configuration before asking questions. Do not ask for facts available in the repository. - Apply
requirements-triageand create a discovery map with:- confirmed facts;
- unknowns;
- assumptions that would affect implementation;
- preferences that affect UX, API shape, rollout, compatibility, or tests;
- decision-changing blockers.
- Ask a structured question batch. Unlike
/spec, this command is intentionally more interrogative:- normally ask 6–12 focused questions;
- never ask more than 15 in one batch;
- group them by product behavior, UX/API/data, edge cases, rollout, and validation;
- mark each question as blocking, recommended, or optional;
- provide a proposed default for every recommended or optional question.
- Wait for the user's answers when any blocking question remains. If the user asks you to proceed with defaults, record those defaults explicitly.
- Select and announce one planning path:
direct-specfor still-small work where detail was needed mainly for clarity;specialist-assisted-specfor cross-cutting work needing one to three specialist planning reviews;full-council-specfor high-risk, irreversible, architectural, security-sensitive, or product-contested work.
- Use
specialist-routingfor any relevant planning reviews. Give specialists the same brief and context capsule. Use isolated parallel reports only where the tool supports native subagents; otherwise use clearly labelled sequential or simulated role passes. - Produce a complete spec with the normal
/specstructure plus these detailed sections:- Decision log — each answered question, chosen default, and reason;
- Alternative behaviors considered — rejected options and why;
- Acceptance examples — concrete examples or scenarios for critical requirements;
- Observability and rollout — metrics, logs, flags, migration, rollback when relevant.
- Save it to
.agent/specs/<kebab-case-name>.mdusing the standard spec frontmatter contract below. - Present a concise plain-language decision summary using
/sum-spec's output contract. Stop and request approval explicitly. Do not start implementation workers.
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.
- 9d ago First seen · 126 lines · 22 tokens per session scan A 20588a7ed6a1
spec-detailed is a command published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 1,146 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.