Workflow Orchestration
vxcozy/workflow-orchestration
Disciplined task execution with planning, verification, and self-improvement loops.
Checks the quality of behavior evidence after each iteration in three tiers, using two auditor subagents in parallel to review the same work and find gaps.
Install Iteration Progress Audit
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install prime-radiant-inc/iterative-development auditing-progress --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/auditing-progress .claude/skills/auditing-progress && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .claude/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progressType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install prime-radiant-inc/iterative-development auditing-progress --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/auditing-progress .agents/skills/auditing-progress && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .agents/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install prime-radiant-inc/iterative-development auditing-progress --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/auditing-progress .cursor/skills/auditing-progress && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .cursor/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/prime-radiant-inc/iterative-development.git --path skills/auditing-progress--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install prime-radiant-inc/iterative-development auditing-progress --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/auditing-progress .gemini/skills/auditing-progress && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .gemini/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install prime-radiant-inc/iterative-development auditing-progressInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/auditing-progress .github/skills/auditing-progress && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .github/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install prime-radiant-inc/iterative-development auditing-progress --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/iterative-development.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/auditing-progress .opencode/skills/auditing-progress && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "auditing-progress" agent skill from https://github.com/prime-radiant-inc/iterative-development/tree/main/skills/auditing-progress into .opencode/skills/auditing-progress/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auditing-progress", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
auditing-progress- GitHub stars
- 181
- Token cost
- ~1.1k tokens
- SKILL.md length
- 464 words
- Files
- 2
- Skills in repo
- 6
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Checks the quality of behavior evidence after each iteration in three tiers, using two auditor subagents in parallel to review the same work and find gaps.
- Works in 5 steps: Partition the audit into three tiers → Dispatch paired auditor subagents (PAR) → Aggregate findings → …
- An iteration just finished and its evidence needs verifying before the next one
- SKILL.md covers Overview, When to Use, Audit Process and Quick Reference, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
It runs after every iteration of the iterative-development cycle, before the next iteration is chosen. The question it answers is whether durable, reusable evidence exists for every externally visible behavior the iteration touched. Work is split into three tiers: deep evidence for stories finished in this iteration and scenarios added or changed, impacted scenarios whose owning stories had code changes, and the sentinel corpus compared against the pre-iteration baseline.
Two auditor subagents receive the same material, wrapped in competitive framing, and review it in parallel using a prompt file shipped with the skill. Their results are merged: a finding from both counts once with high confidence, a finding from one is kept as actionable, and when severity differs the more severe rating wins. If gaps appear, the agent adds gap stories to the requirements files as pending or moves finished stories back to pending.
When your agent uses it
- An iteration just finished and its evidence needs verifying before the next one
- Checking that touched behavior scenarios still pass
- Detecting regressions in a sentinel set of high-value scenarios
Example prompts
- “Audit the progress of the iteration we just finished and list any evidence gaps.”
- “Run the three-tier audit and tell me which stories should go back to pending.”
Requirements
- The iterative-development plugin's requirements and behavior scenario files
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c05889a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Iteration Progress Audit loads about 1.1k tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 464 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from prime-radiant-inc/iterative-development at commit c05889a, republished under its Apache-2.0 licence (© prime-radiant-inc). 464 words, ~1,056 tokens.
Download SKILL.mdSave it as
.claude/skills/auditing-progress/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- auditing-progress
- description
- Use when an iteration has just finished and you need to verify behavior evidence quality in three tiers — deep evidence for current stories, impacted behavior for touched scenarios, and sentinel corpus for high-value regression detection.
Auditing Progress
Overview
Runs after every iteration as part of the planning cycle. Verifies behavior evidence quality in three tiers using parallel adversarial review (PAR) — two paired auditor subagents evaluate the same work in parallel with competitive framing.
The audit answers: "Does durable, reusable evidence exist at the correct seam for every externally observable behavior this iteration touched?"
When to Use
Invoked by iterative-development after every running-an-iteration call, before picking the next iteration.
Audit Process
1. Partition the audit into three tiers
Read the per-epic requirement files in docs/superpowers/iterations/requirements/, docs/superpowers/iterations/behavior-scenarios.md, and docs/superpowers/iterations/behavior-corpus.md:
- Tier 1 — Deep evidence: stories marked
done:ITER-<current>and scenarios added or updated in this iteration. Audit every AC and its proof obligation thoroughly. - Tier 2 — Impacted behavior: all existing scenarios whose owning stories had code changes in this iteration (even if those stories were completed in earlier iterations). Verify the scenarios still pass.
- Tier 3 — Sentinel corpus: all scenarios with run cadence
sentinelin the behavior corpus. Compare against the pre-iteration baseline fromrunning-an-iterationstep 3.
2. Dispatch paired auditor subagents (PAR)
Following the PAR methodology in skills/shared/parallel-adversarial-review.md:
- Build the auditor prompt using
auditor-subagent-prompt.md. Include ALL THREE tiers:- Tier 1: full story cards with proof obligations + new/changed scenario cards
- Tier 2: impacted scenario cards + their current test results
- Tier 3: sentinel scenario IDs + baseline results + current results
- Wrap in competitive framing from
skills/shared/par-reviewer-wrapper.md - Dispatch TWO auditor subagents in parallel
- Wait for both to return
3. Aggregate findings
Following PAR aggregation rules:
- Same finding from both auditors → one finding, high confidence
- Finding from only one auditor → separate finding, still actionable
- Severity disagreement → take the more severe assessment, always fix it
Show full SKILL.md (189 more words)Show less
4. Process results
- If gaps found (any AC fails, evidence is too weak, sentinel regression detected):
- For AC failures: append gap stories to
requirements/(statuspending) or flip existing stories back fromdonetopending - For weak evidence: create evidence-improvement stories (add scenario, strengthen seam)
- For sentinel regressions: create regression-fix stories with CRITICAL priority
- Revise
roadmap.mdto add a follow-up iteration for the gaps
- For AC failures: append gap stories to
- If clean (all tiers pass, evidence is adequate):
- The iteration is confirmed done
- Return clean signal to the orchestrator
5. Return control
Return the audit result (clean or gaps) to the orchestrator. The orchestrator decides whether to loop or terminate.
Quick Reference
| Tier | What it checks | Failure means |
|---|---|---|
| Deep evidence | Every AC + proof obligation for current iteration | Story not done, evidence too weak |
| Impacted behavior | Scenarios whose surfaces were touched | Stale or broken scenario |
| Sentinel corpus | High-value journey scenarios | Regression in previously-working behavior |
| Reads | Writes | Dispatches |
|---|---|---|
requirements/, behavior-scenarios.md, behavior-corpus.md, product code/tests | requirements/ (gaps), roadmap.md (new iteration) if gaps, behavior-scenarios.md (stale flags) | Two auditor subagents in parallel (PAR) |
References
skills/shared/parallel-adversarial-review.md— PAR methodologyskills/shared/par-reviewer-wrapper.md— competitive framing wrapperskills/shared/behavior-evidence-formats.md— scenario and proof obligation formatsauditor-subagent-prompt.md— auditor-specific prompt template
© prime-radiant-inc, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/auditing-progress of prime-radiant-inc/iterative-development.
- SKILL.md
- auditor-subagent-prompt.md
Open the folder on GitHubat commit c05889a
Compare with similar skills
Iteration Progress Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Iteration Progress Audit this skillprime-radiant-inc/iterative-development | 181 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Workflow Orchestrationvxcozy/workflow-orchestration | 116 | — | ~1k | Automated safety check: Pass | MIT | |
| Loop Change Verifiercobusgreyling/loop-engineering | 11k | 1 repos | ~383 | Automated safety check: Pass | MIT | |
| Verification Skill Maintenancecursor/plugins | 10k | 8 repos | ~1.2k | Automated safety check: Pass | None | |
| Verify and StopJuliusBrussee/caveman | 111k | 1 repos | ~176 | Automated safety check: Pass | Apache-2.0 | |
| Verification Before CompletionjnMetaCode/superpowers-zh | 8.3k | — | ~443 | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Iteration Progress Audit
What does Iteration Progress Audit do?
Checks the quality of behavior evidence after each iteration in three tiers, using two auditor subagents in parallel to review the same work and find gaps. It runs after every iteration of the iterative-development cycle, before the next iteration is chosen. The question it answers is whether durable, reusable evidence exists for every externally visible behavior the iteration touched.
When should I use Iteration Progress Audit?
Iteration Progress Audit fits situations like: an iteration just finished and its evidence needs verifying before the next one; checking that touched behavior scenarios still pass; detecting regressions in a sentinel set of high-value scenarios.
How do I install Iteration Progress Audit in Claude Code?
Run `npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a claude-code`. Or copy the skill folder (skills/auditing-progress in prime-radiant-inc/iterative-development) into .claude/skills/auditing-progress in your project. Claude Code loads it when a task matches its description.
How do I install Iteration Progress Audit in Codex?
Run `npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a codex`. Or copy the skill folder (skills/auditing-progress in prime-radiant-inc/iterative-development) into .agents/skills/auditing-progress in your project. Codex loads it when a task matches its description.
Can I use Iteration Progress Audit in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add prime-radiant-inc/iterative-development --skill auditing-progress -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auditing-progress, .gemini/skills/auditing-progress, .github/skills/auditing-progress and .opencode/skills/auditing-progress in your project.
What does Iteration Progress Audit need to run?
SKILL.md names no scripts, command-line tools or credentials: Iteration Progress Audit is instructions for the agent only. Our summary lists: The iterative-development plugin's requirements and behavior scenario files.
Does Iteration Progress Audit access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Iteration Progress Audit safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Iteration Progress Audit use?
Iteration Progress Audit is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Iteration Progress Audit use?
About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Iteration Progress Audit?
Skills that share tags, products or a category with Iteration Progress Audit: Workflow Orchestration (vxcozy/workflow-orchestration, 116 stars), Loop Change Verifier (cobusgreyling/loop-engineering, 11k stars), Verification Skill Maintenance (cursor/plugins, 10k stars) and Verify and Stop (JuliusBrussee/caveman, 111k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Iteration Progress Audit?
prime-radiant-inc (a GitHub organization) maintains it in prime-radiant-inc/iterative-development, which has 181 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on June 6, 2026.
Source: prime-radiant-inc/iterative-development on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.