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 commands/dilawarshafiq/unworldly/sp.plangit clone --depth 1 https://github.com/DilawarShafiq/unworldlyWrote 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/dilawarshafiq/unworldly/sp.plan)<a href="https://agentmods.dev/commands/dilawarshafiq/unworldly/sp.plan"><img src="https://agentmods.dev/badge/commands/dilawarshafiq/unworldly/sp.plan.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 | $0.00014 | $0.01089 |
| Opus 5 | $0.00007 | $0.00544 |
| Sonnet 5 | $0.00003 | $0.00218 |
| Haiku 4.5 | $0.00001 | $0.00109 |
Grade A, and why
sp.plan 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 5d 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.
This is a copy
80% identical to speckit.plan — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Outline
-
Setup: Run
.specify/scripts/powershell/setup-plan.ps1 -Jsonfrom repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot"). -
Load context: Read FEATURE_SPEC and
.specify/memory/constitution.md. Load IMPL_PLAN template (already copied). -
Execute plan workflow: Follow the structure in IMPL_PLAN template to:
- Fill Technical Context (mark unknowns as "NEEDS CLARIFICATION")
- Fill Constitution Check section from constitution
- Evaluate gates (ERROR if violations unjustified)
- Phase 0: Generate research.md (resolve all NEEDS CLARIFICATION)
- Phase 1: Generate data-model.md, contracts/, quickstart.md
- Phase 1: Update agent context by running the agent script
- Re-evaluate Constitution Check post-design
-
Stop and report: Command ends after Phase 2 planning. Report branch, IMPL_PLAN path, and generated artifacts.
Phases
Phase 0: Outline & Research
-
Extract unknowns from Technical Context above:
- For each NEEDS CLARIFICATION → research task
- For each dependency → best practices task
- For each integration → patterns task
-
Generate and dispatch research agents:
For each unknown in Technical Context: Task: "Research {unknown} for {feature context}" For each technology choice: Task: "Find best practices for {tech} in {domain}" -
Consolidate findings in
research.mdusing format:- Decision: [what was chosen]
- Rationale: [why chosen]
- Alternatives considered: [what else evaluated]
Output: research.md with all NEEDS CLARIFICATION resolved
Phase 1: Design & Contracts
Prerequisites: research.md complete
- Extract entities from feature spec →
data-model.md:- Entity name, fields, relationships
- Validation rules from requirements
- State transitions if applicable
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.
- 5d ago First seen · 116 lines · 14 tokens per session scan A 0ca695cde144
sp.plan is a command published in the GitHub repository DilawarShafiq/unworldly (9 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 1,089 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to speckit.plan, differing in 34 lines, and is treated as a copy.
Other commands, from other repositories
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doctor
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capture-feedback
Quick feedback capture with structured signals.
check-gates
Run a Pre-Action Gate check against prevention rules before executing a risky action.
integrate
/forge:integrate is the integration assistant for connecting your project to external services. It covers version control (GitHub, GitLab), monitoring (Sentry, Datadog), communication (Slack, Discord), databases (PostgreSQL, Redis, MongoDB), and cloud platforms (AWS, GCP, Vercel, Netlify). For each service, it checks…