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/SteveGJones/ai-first-sdlc-practicesWrote 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/stevegjones/ai-first-sdlc-practices/v020-design-decisions-review)<a href="https://agentmods.dev/commands/stevegjones/ai-first-sdlc-practices/v020-design-decisions-review"><img src="https://agentmods.dev/badge/commands/stevegjones/ai-first-sdlc-practices/v020-design-decisions-review/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/stevegjones/ai-first-sdlc-practices/v020-design-decisions-review"><img src="https://agentmods.dev/badge/commands/stevegjones/ai-first-sdlc-practices/v020-design-decisions-review.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 | $0.00000 | $0.00731 |
| Opus 5 | $0.00000 | $0.00365 |
| Sonnet 5 | $0.00000 | $0.00146 |
| Haiku 4.5 | $0.00000 | $0.00073 |
Grade A, and why
v020-design-decisions-review 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 12d 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.
v0.2.0 Phase A Design Decisions Review
Your Role
You are a senior solution architect conducting an INDEPENDENT architectural review of the v0.2.0 Phase A design-decisions addendum. This addendum locks six architectural calls before any implementation begins (Phases B-G of EPIC #188). Getting these right matters — Phases B-G must not relitigate any decision; mid-implementation corrections require controller escalation.
You operate in a fresh container with SDLC plugins installed. Use the
sdlc-team-common:solution-architect agent (via the Agent tool with
subagent_type="sdlc-team-common:solution-architect") for the architectural review.
What you're reviewing
Primary input: docs/superpowers/specs/2026-05-01-v020-design-decisions.md (the addendum).
Required reading:
docs/superpowers/specs/2026-05-01-v020-assured-improvements-design.md— EPIC #188 scope- The addendum itself (
docs/superpowers/specs/2026-05-01-v020-design-decisions.md) research/phase-f-dogfood-findings.md— the 10 findings the design decisions resolve- The relevant v0.1.0 modules:
plugins/sdlc-assured/scripts/assured/code_index.pyplugins/sdlc-assured/scripts/assured/decomposition.pyplugins/sdlc-assured/scripts/assured/traceability_validators.pyplugins/sdlc-assured/scripts/assured/ids.pyplugins/sdlc-assured/scripts/assured/export.py
What to do
Dispatch the sdlc-team-common:solution-architect agent with the prompt below.
Prompt to dispatch
You are conducting an INDEPENDENT architectural review of the v0.2.0 Phase A
design-decisions addendum at docs/superpowers/specs/2026-05-01-v020-design-decisions.md.
Required reading:
- docs/superpowers/specs/2026-05-01-v020-assured-improvements-design.md (EPIC #188 scope)
- The addendum itself (the file under review)
- research/phase-f-dogfood-findings.md (the 10 findings the design decisions resolve)
- The relevant v0.1.0 modules in plugins/sdlc-assured/scripts/assured/{code_index,decomposition,traceability_validators,ids,export}.py
Answer 6 questions, one per design decision in the addendum. For each: AGREE / AGREE-WITH-CONCERNS / DISAGREE / NEEDS-REWORK with rationale.
Then SUMMARY: is the Phase A exit criterion met (no downstream semantic
decision remains open)? Are there hidden decisions the addendum missed?
End by writing your verbatim review to:
research/sdlc-bundles/dogfood-workflows/v020-design-decisions-review-output.md
Read-only review. Do NOT modify code or specs.
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.
- 12d ago First seen · 64 lines · 0 tokens per session scan A 83ef41439839
v020-design-decisions-review is a command published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 731 tokens. 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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