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SKILL verified MIT Self-run

Sprint

skill-maxenko-claude-skills-sprint · by maxenko

End-to-end workflow that takes a feature request (or any coding task) and drives it from framing to a machine-verified, adversarially-reviewed diff — pausing only at the two decisions that are the human's (approve the plan, accept the result). Use when the user says 'sprint', '/sprint', hands over a feature request, or wants the full plan-through-verified-change arc. The upgraded successor to dev…

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Install

$ agentstack add skill-maxenko-claude-skills-sprint

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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26d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Sprint — request → verified, review-clean change

Drive $ARGUMENTS from framing to a machine-verified, adversarially-reviewed change.

The reframe this encodes: writing code is cheap; trusting it is the bottleneck. So the rigor lives on the diff (the code that will run), not the plan (a prediction). Governing rule: **the human decides what, the agent decides how, a machine-checked signal decides done.**

This is the upgraded devloop. What changed, and why:

  • It does not end at "implemented." The heavy adversarial pass runs on the DIFF, in

fresh context, with the test output in hand — a reviewer that didn't write the code and has no sunk-cost attachment. That is the single highest-value pass.

  • Critics are grounded. Every objection ties to something checkable (a test it proposes,

a failure it demonstrates). Ungrounded self-critique degrades accuracy; grounded critique finds real defects regardless of which model found them.

  • Loops are bounded correctly. Ungrounded loops (plan critique) cap at ≤2 rounds

more rounds entrench errors, they don't fix them. Grounded loops (fix → re-run the check) run until the signal is green, because each iteration has new ground truth.

  • Findings become permanent guards. Every confirmed defect is converted to a test or a

demo harness before it's fixed, so the failure mode can never silently return.

Single-model Claude throughout — a concrete defect with a reproduction is verifiable on its own merits; you do not need cross-model vote independence to find bugs, only fresh context, divergent lenses, and a "show me the repro" bar.


Phase 0 — Right-size (always first)

Before any machinery, judge the scope. Skip the ceremony when the work is obvious.

| Tier | What it is | What runs | |------|-----------|-----------| | Trivial | One-line / config / rename / obvious fix | Just do it → verify (Phase 5) → done. No plan, no panel. | | Small | Single concern, one file or two | Light spec → implement → verify → quick diff-review. Skip the plan panel. | | Standard | Multi-file feature or refactor | Full arc below. | | Large | System-level / multi-stream | Full arc; plan and diff-review fan out to parallel subagents. |

State the tier in one line and proceed. When in doubt between two tiers, round down — you can always escalate. Plan mode on a one-line fix is pure overhead.


Phase 1 — Frame & name the check

Restate $ARGUMENTS as an outcome, not a task list. Then do the one thing that makes everything after it work:

Name the machine-checkable success criterion. What command, test, or observable proves this is done? (cargo test passes; a new test asserts X; the app drives through flow Y with no console/network errors.) This is what lets the agent self-verify instead of stopping when work merely looks done. If you cannot name a check, that is the first thing to fix — either design one, or ask the user what "done" means here. Do not proceed without it.

If the request is ambiguous, interview the user briefly (2–3 questions) before planning. Keep the spec lightweight — inline for Small, a short plan/*.md for Standard+.


Phase 2 — Plan (Standard+ only)

Invoke plan-feature (or plan-ultra for large multi-stream work) to produce a phased, vertically-sliced plan in plan/*. Small reviewable slices — review capacity is the real bottleneck. Each slice states its own done-criterion (tie back to the Phase 1 check).


Phase 3 — Plan critique + approval gate

Invoke plan-eval on the plan. Bounded to ≤2 rounds of refinement — grounded critique converges fast; if two rounds don't land a SOLID verdict, stop and surface the disagreement to the user rather than grinding a polluted context.

■ HUMAN GATE — plan approval. Present the plan and enter plan mode; do not write code until the user approves. This gate is a strength of the old flow — keep it.


Phase 4 — Implement in slices

Work the approved plan slice by slice. After each slice, run the Phase 1 check — don't batch verification to the end. Honor the project's invariants (read its CLAUDE.md); a generic implementer misses house-specific footguns unless they're in front of it.


Phase 5 — Verify against the runnable check

Nothing is "done" until the check passes. Discover it (in priority order): the criterion named in Phase 1 → a project verify skill → the obvious build/test command for the stack (cargo test, npm test, …).

For UI / runtime changes, drive the real app and look — do not assert behavior from the source or the DOM. Use the project's own verification path (read CLAUDE.md: e.g. this repo drives the running window with tools/ui_probe.ps1 + AL_* demo harnesses + in-page document::eval dispatch — not Playwright, which cannot reach a native desktop WebView). Pattern: agent explores, code judges — the agent exercises the running software; the agent checks console + network errors; deterministic assertions decide pass/fail. Demand evidence (command output, screenshots), not claims.


Phase 6 — Diff-review in FRESH context (the center of gravity)

Spawn fresh subagent(s) — via Agent for Small, or a Workflow fan-out for Standard+ (≤10 in flight). They must NOT be the context that wrote the code. Give each subagent ONLY, inline (a subagent sees only its dispatch prompt):

  1. The diffgit diff of the change under review.
  2. The check output — the passing (or failing) test/build result from Phase 5.
  3. The project's invariants — the relevant CLAUDE.md rules as an explicit checklist

(for this repo: theming/var() re-patch traps, the perf-scaling governance rules, layout invariants, FPL doc-sync). This is what turns a generic critic into one that finds real defects — the panel is smart because you feed it the domain.

Point your existing code-scrutiny / bug-hunt muscle at the diff, one per lens (correctness & error paths; the project's known footguns; perf / resource scaling). Each finding must carry a concrete failing input/state → observable consequence — no style-only or speculative findings. "No issues found" is a valid, preferred outcome.


Phase 7 — Regression capture

For every confirmed finding, add a permanent guard — a unit test, or a demo/probe harness for UI — that fails on the defect before you fix it. The real endpoint of the loop is not "review passed"; it's "the failure mode review caught can never silently return." This is the highest-compounding habit in the whole flow.


Phase 8 — Fix loop (grounded — run to green)

Fix the confirmed findings, then re-run the Phase 5 check + the new Phase 7 guards. Repeat until green. This loop is grounded — each pass has a fresh, real signal — so it is not capped at 2; run it until the check is clean. (The ≤2 cap applies only to ungrounded rumination, e.g. re-critiquing the plan with no new signal.)

■ HUMAN GATE — accept. Report back, succinct and structured:

  • what was built (against the outcome from Phase 1),
  • the green-check evidence (output / screenshots),
  • each confirmed finding, how it was resolved, and the guard now protecting it,
  • anything deferred, and why.

The panel advises; the human decides. Commit only when asked (respect the repo's commit conventions — branch off the default branch if needed).


Loop discipline (the rule that governs every phase)

  • Ungrounded loop = revising an answer with no new external signal (re-critiquing a plan,

self-correcting prose). Converges in 1–2 rounds, then entrenches errors. Cap at ≤2. If it's not landing, /clear + re-prompt beats grinding a polluted context.

  • Grounded loop = each iteration has new ground truth (a failing test, a new repro, real

execution output). Run to green. Bounding this one is a mistake.

What this reuses (don't reinvent — conduct)

| Phase | Delegates to | |-------|-------------| | Plan | plan-feature / plan-ultra | | Plan critique | plan-eval | | Diff-review | code-scrutiny / bug-hunt in fresh subagents | | Verify (UI) | project verify skill / tools/ui_probe.ps1 + demo harnesses |

The five judgments that stay with the human (never automated)

  1. Is this task big enough to bother with the machinery? (Phase 0)
  2. What does "done" look like? (Phase 1 — you define the check; the flow enforces it)
  3. How much do I trust it to run alone here? (autonomy between the two gates)
  4. Is it stuck? (know when to /clear and restart)
  5. Do I actually agree with the panel? (it advises; you decide — the accept gate)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.