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/loiane/specs-driven-development-spring-angular/plangit clone --depth 1 https://github.com/loiane/specs-driven-development-spring-angularWhat 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 | $0.00018 | $0.01063 |
| Opus 5 | $0.00009 | $0.00531 |
| Sonnet 5 | $0.00004 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
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 yesterday.
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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/plan
Phase: 3 — plan
Owning agent: .claude/agents/spring-architect.md
Skills used: epic-slicing-planning, spring-task-decomposition, spring-boot-4-conventions, openapi-contract-first, flyway-or-liquibase-detection, archunit-rules, adr-authoring, performance-optimization
Stack routing
| Feature scope | Agent |
|---|---|
| Backend-only or full-stack (Spring) | spring-architect (this agent) |
| Frontend-only (Angular) | angular-architect |
| Full-stack | Run both: spring-architect for backend tasks, angular-architect for frontend tasks |
If the feature's 01-spec.md ACs reference only Angular/UI concerns (components, routes, templates, styles), delegate entirely to angular-architect. If ACs span both stacks, produce a unified 03-design.md but decompose 04-tasks.md into backend tasks (owned by spring-architect) and frontend tasks (owned by angular-architect).
Purpose
Translate a PASS-verdict spec into planning artifacts:
- Non-Epic mode:
03-design.md+04-tasks.md - Epic mode:
03-epic-design.md+03a-epic-roadmap.md, then slice-level03-design.md+04-tasks.md
Then initialize .tdd-state.json.
Inputs
<feature-id>.- Optional
--epicto force Epic mode.
Reads
01-spec.md,02-spec-review.md(verdict must bePASS)..specs/_stack.json..claude/templates/design.template.md,.claude/templates/tasks.template.md,.claude/templates/adr.template.md.- Epic mode:
.claude/templates/epic-design.template.md,.claude/templates/epic-roadmap.template.md. - All design/architecture skills above.
Writes
.specs/<feature-id>/03-epic-design.md(Epic mode).specs/<feature-id>/03a-epic-roadmap.md(Epic mode).specs/<feature-id>/03-design.md.specs/<feature-id>/04-tasks.md.specs/<feature-id>/.tdd-state.json(initial: noactive_task, every taskphase: "pending").specs/<feature-id>/adr/ADR-NNN-*.mdfor any architecturally significant decision.
Process
- Refuse if
02-spec-review.mdis missing or its verdict is notPASS. - Refuse if
01-spec.mdstill has anyQ-NNN. - Detect planning mode. Use Epic mode if
--epicis present or the feature spans multiple vertical slices/shared cross-cutting decisions. - In Epic mode, write
03-epic-design.mdand03a-epic-roadmap.mdfirst. Refuse to continue if either Epic artifact has unresolvedQ-NNN. - Produce
03-design.md: module map, public API, REST contract sketch (or full OpenAPI), data model, migration plan (Flyway/Liquibase per_stack.json), error model, observability, security touch points, ArchUnit rule additions. - For each architecturally-significant choice, write an ADR.
- Decompose into tasks
T-001,T-002, ... Each task must list:id,title,acs_covered: [AC-NNN, ...],files_in_scope: [paths],depends_on,estimated_phases: [red, green, refactor, simplify].- Tasks that touch
src/main/**MUST list at least one file undersrc/test/**infiles_in_scope.
- Validate AC coverage: every AC from
01-spec.mdmust appear in at least one task. If not, FAIL the plan and surface the gap. - Initialize
.tdd-state.json:{ "active_task": null, "tasks": { "T-001": { "phase": "pending", "files_in_scope": [...], "acs_covered": [...] }, ... } }
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.
- yesterday First seen · 73 lines · 18 tokens per session scan A 962bf59c0619
plan is a command published in the GitHub repository loiane/specs-driven-development-spring-angular (57 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 1,063 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.
Other commands, from other repositories
devkit.refactor
Provides guided code refactoring capability with deep codebase understanding, compatibility options, and comprehensive verification. Use when restructuring or improving existing code.
spec-kitty.analyze
Spec-Driven Development for serious software developers. Spec Coding with with Claude, Cursor, Gemini, Codex. Kanban dashboard, git worktrees, auto-merge and more.
devkit.verify-skill
Validates a skill against DevKit standards (requirements, template, dependencies). Use when you need to verify a skill before publishing or after modifications.
devkit.prompt-optimize
Provides expert prompt optimization using advanced techniques (CoT, few-shot, constitutional AI) for LLM performance enhancement. Use when you need to improve prompt quality or optimize LLM interactions.
sdd-plan
Turn a spec into a persisted baby-step plan file — research, resume, impact analysis.
sdd-architecture-update
Detect architecture drift and sync the snapshot + Memory Bank (with confirmation).