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/mostashraf/ai-sdlc-harness/improvegit clone --depth 1 https://github.com/MostAshraf/ai-sdlc-harnessWrote 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/mostashraf/ai-sdlc-harness/improve)<a href="https://agentmods.dev/commands/mostashraf/ai-sdlc-harness/improve"><img src="https://agentmods.dev/badge/commands/mostashraf/ai-sdlc-harness/improve.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 | $0.00000 | $0.00703 |
| Opus 5 | $0.00000 | $0.00351 |
| Sonnet 5 | $0.00000 | $0.00141 |
| Haiku 4.5 | $0.00000 | $0.00070 |
Grade A, and why
improve 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/story-workflow improve
Single-pass story improvement — assess readiness internally, fill gaps conversationally, and produce a refined story, all in one adaptive flow. This is the recommended default: it replaces the separate analyze-then-refine dance.
Steps
- Fetch the work item per
shared/provider-io.md(title, description, acceptance criteria, state, links). If it isn't found, stop. - Load
templates/story-template.md(target format),templates/readiness-report.md(used only as an internal rubric — do not present a standalone report), andshared/context.mdfor domain language. - Assess readiness internally against the rubric, then classify into a tier:
- Tier 1 — Solid: ≤1–2 yellow flags, no red. Draft immediately.
- Tier 2 — Some gaps: 1–3 issues. Specific areas need clarification.
- Tier 3 — Rough: 4+ issues, or a whole section missing (no ACs, no description). Needs substantial input.
- Fill gaps conversationally, adapted to the tier:
- Tier 1: skip questions, acknowledge what's good, draft.
- Tier 2: ask 2–5 targeted questions — each references the specific gap and proposes an answer to confirm or correct (the user validates, not drafts). Present them all at once.
- Tier 3: say so honestly, ask up to 5 questions, then (if critical gaps remain) one more round of up to 3, then draft.
- Session notes (passed after the id) are gold: mine them before asking anything, and don't ask what they already answer. If none and the story is Tier 2/3, ask once whether any exist.
- Draft the whole story at once in
templates/story-template.md: Context, Description, Acceptance Criteria (happy path then error/edge), Out of Scope, Open Questions ([PO]/[Tech]/[Team]), and an empty Technical Notes (that'sgroom's). For Tier 2/3, prepend a short "What was improved" list; skip it for Tier 1. - Review and iterate — present the full draft, adjust any section the user flags. If it's grown too large (>7 ACs, multiple capabilities), suggest a split. After minor edits, just confirm the change; don't re-dump the story.
- Post on approval per
shared/provider-io.md— one comment carrying the "What was improved" summary (if any) plus the full story. Forlocal-markdown, offer the in-place overwrite of the source file (this command is one of the two that may rewrite a story in place).
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 · 48 lines · 0 tokens per session scan A f953ccbeadb3
improve is a command published in the GitHub repository MostAshraf/ai-sdlc-harness (18 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 703 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.
Other commands, from other repositories
add-phase
Add phase to end of current milestone in roadmap.
insert-phase
Insert urgent work as decimal phase (e.g., 72.1) between existing phases.
reapply-patches
Reapply local modifications after a PBR update.
remove-phase
Remove a future phase from roadmap and renumber subsequent phases.
research-phase
Research how to implement a phase (standalone — usually use /pbr:plan-phase instead).
update
Update PBR to latest version with changelog display.