Agent skill

Iterating

by oaustegard in oaustegard/claude-skills

Multi-conversation methodology for iterative stateful work with context accumulation.

MITAuto-check passedDevelopment

Install Iterating

skills CLI
$ npx skills add oaustegard/claude-skills --skill iterating -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install oaustegard/claude-skills iterating --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/iterating .claude/skills/iterating && rm -rf skills-src

Use ~/.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/

Facts

Skill name
iterating
GitHub stars
150
Token cost
~1.8k tokens
SKILL.md length
602 words
Files
8 (incl. references)
Skills in repo
69
Repo updated
First seen
Licence
MIT

At a glance

Multi-conversation methodology for iterative stateful work with context accumulation.

  • Works in 5 steps: Create/Update WorkLog → Output for user… → User saves WorkLog to project knowledge… → User says "continue" (same or new… → …
  • Users request work that spans multiple sessions (research
  • SKILL.md covers Environment Detection, Checkpoint Pattern, WorkLog Format and Core Workflow, plus 9 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Iterating is an agent skill from oaustegard/claude-skills. Multi-conversation methodology for iterative stateful work with context accumulation. Use when users request work that spans multiple sessions (research, debugging, refactoring, feature development), need to build on past progress, explicitly mention iterative work, work logs, project knowledge, or cross-conversation learning.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `CHANGELOG.md`, `README.md` and `references/advanced-patterns.md`).

It sits in Development, covering Refactoring. The repository describes itself as: My collection of Claude skills. The licence is MIT.

When your agent uses it

  • Users request work that spans multiple sessions (research
  • Feature development)
  • Need to build on past progress
  • Explicitly mention iterative work

Example prompts

  • “/iterating”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Create/Update WorkLog → Output for user → STOP
  2. User saves WorkLog to project knowledge (survives conversation limits)
  3. User says "continue" (same or new conversation)
  4. Make incremental progress on ONE item → Update WorkLog → STOP
  5. Repeat

What it can do on your machine

Read from SKILL.md and the folder at commit 6fc82b8. 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 (its code samples are markdown and bash).

    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

Iterating loads about 1.8k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 602 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

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 oaustegard/claude-skills at commit 6fc82b8, republished under its MIT licence (© oaustegard). 602 words, ~1,776 tokens.

Download SKILL.mdSave it as .claude/skills/iterating/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
iterating
description
Multi-conversation methodology for iterative stateful work with context accumulation. Use when users request work that spans multiple sessions (research, debugging, refactoring, feature development), need to build on past progress, explicitly mention iterative work, work logs, project knowledge, or cross-conversation learning.
metadata.version
1.2.0

Iterating

Maintain context across multiple sessions by persisting state in Work Logs.

Environment Detection

Detect environment and load appropriate reference:

bash
if [ "$CLAUDE_CODE_REMOTE" = "true" ]; then
  # Claude Code on the Web (CCotw) - writes to GitHub
  # Read: references/ccotw-environment.md
elif [ -n "$CLAUDE_CODE_REMOTE" ]; then
  # Claude Code CLI - writes to local filesystem
  # Read: references/codecli-environment.md
elif [ -x "$(command -v osascript)" ] && [ -d "/Applications/Claude.app" ]; then
  # Claude Desktop - may write to disk OR output for download
  # Read: references/desktop-environment.md
else
  # Claude.ai (web/chat/native app) - outputs for download
  # Read: references/chat-environment.md
fi

See environment-specific reference for persistence and retrieval details.

Checkpoint Pattern

The iterating skill enforces a checkpoint-and-save pattern to prevent work loss:

  1. Create/Update WorkLog → Output for user → STOP
  2. User saves WorkLog to project knowledge (survives conversation limits)
  3. User says "continue" (same or new conversation)
  4. Make incremental progress on ONE item → Update WorkLog → STOP
  5. Repeat

This matters because separate conversations don't share context automatically: skipping the STOP step ("full waterfall") produces work the user hasn't seen or been able to redirect, and risks losing everything mid-task if the conversation ends before a checkpoint lands.

WorkLog Format

markdown
---
version: v1
status: in_progress
---

# [Project Name] Work Log

## v1 | YYYY-MM-DD HH:MM | Title

**Prev:** [previous context OR "Starting new work"]
**Now:** [current goal]

**Progress:** [X% complete OR milestone status]

**Files:**
- `path/to/file.ext` (Why this file matters)
  - L45-67: [What to examine/change here]
  - L123-145: [Another area, specific issue]

**Work:**
+: [additions with file:line]
~: [changes with file:line]
!: [fixes with file:line]

**Decisions:**
- [what]: [why] (vs [alternatives])

**Works:** [effective approaches]
**Fails:** [ineffective approaches, why]

**Blockers:** [None OR specific blocker with owner/ETA]

**Next:**
- [HIGH] [Critical action item]
- [MED] [Important but not urgent]
- [LOW] [Nice to have]

**Open:** [questions needing answers]

Core Workflow

Starting new work:

  1. Detect environment
  2. Create WorkLog v1 with task objective, decisions, file references, next steps
  3. Persist using environment-specific method
  4. STOP - Present WorkLog to user
    • Explain what's planned
    • Tell user to save WorkLog to project knowledge
    • Wait for user to say "continue" before starting work

Continuing work:

  1. Detect environment
  2. Retrieve WorkLog using environment-specific method OR recognize pasted WorkLog
  3. Parse latest version and status
  4. Acknowledge: "From WorkLog vN, status: [status]. Progress: [X%]. Working on: [specific HIGH item]"
  5. Execute ONE HIGH priority item.
  6. Update WorkLog, increment version
  7. Persist using environment-specific method
  8. STOP - Present updated WorkLog to user
    • Summarize what was completed
    • Tell user to save updated WorkLog
    • Wait for user to say "continue" before next item

Recognizing pasted WorkLog: If user pastes content with WorkLog frontmatter at conversation start:

  1. Parse version and status from YAML
  2. Acknowledge: "From WorkLog vN, status: [status]. Task: [objective]. Next: [HIGH item]"
  3. Continue workflow from step 5 above

Version Management

  • Simple incremental: v1 → v2 → v3
  • Frontmatter: version: vN (required)
  • Filename: WorkLog vN.md (optional)
  • Multiple files: Use highest version number

Status States

  • in_progress: Active work continuing
  • blocked: Waiting on external dependency/decision
  • needs_review: Ready for human inspection
  • completed: Task finished

Priority System

Next steps must be prioritized:

  • [HIGH]: Critical items blocking other work
  • [MED]: Important but not urgent
  • [LOW]: Nice-to-have improvements

Claude works on one HIGH priority item per iteration (see Core Workflow above) unless told otherwise — this keeps each checkpoint reviewable instead of bundling several changes into one WorkLog update.

Show full SKILL.md (225 more words)Show less

File References

Use relative paths from project root with line ranges:

markdown
**Files:**
- `src/auth/oauth.ts` (OAuth implementation needs refactoring)
  - L45-67: Current token validation logic
  - L123-145: Refresh token handling (race condition on L134)

Critical: Use relative paths, NOT absolute /home/claude/ paths (fresh compute each session).

Progress Tracking

Always include progress indicators (token/quota constraints may prevent completing full plan):

markdown
**Progress:** 60% complete

Or for longer projects:

markdown
**Progress:** Phase 2/3 | Auth ✅ | Payments 50% 🔄 | UI ⏳

What to Document

Include:

  • Key decisions with rationale and alternatives
  • Effective and ineffective approaches
  • Important discoveries
  • File references with line ranges
  • Next steps with priorities
  • Progress indicators
  • Blockers with owner/ETA

Don't include:

  • Minor code changes (use git)
  • Obvious information
  • Raw data dumps
  • Implementation details (use code comments)

User Communication

After creating WorkLog:

  • "Created WorkLog v1. Please save this to project knowledge."
  • "Ready to start when you say 'continue'."

After completing an item:

  • "Completed [item]. Updated WorkLog to vN."
  • "Please save updated WorkLog to project knowledge."
  • "Ready for next item when you say 'continue'."

When continuing:

  • "From WorkLog vN, status: [status]. Progress: [X%]."
  • "Working on: [specific HIGH item]"

Status changes:

  • "Updated WorkLog status to [new_status]: [reason]"
  • "Please save updated WorkLog."

Advanced Patterns

Read references/advanced-patterns.md when:

  • Working on projects spanning 5+ sessions
  • User mentions "debugging strategy", "hypothesis tracking", or "decision evolution"
  • Managing multiple concurrent workstreams
  • User asks about long-running project patterns
  • Blocked on complex issues requiring systematic approach

Otherwise skip - basic workflow above is sufficient for most cases.

Reference Documentation

© oaustegard, MIT. 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 7 other files (references) in iterating of oaustegard/claude-skills.

  • SKILL.md
  • CHANGELOG.md
  • README.md
  • references/advanced-patterns.md
  • references/ccotw-environment.md
  • references/chat-environment.md
  • references/codecli-environment.md
  • references/desktop-environment.md

Open the folder on GitHubat commit 6fc82b8

Compare with similar skills

Iterating 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.

Iterating compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Iterating this skilloaustegard/claude-skills150—~1.8kAutomated safety check: PassMIT
Guidelinesakash-network/node1.1k22 repos~577Automated safety check: PassMIT
Component Refactoringlangflow-ai/langflow156k—~3.5kAutomated safety check: PassMIT
Migrate Core Code to Submodulestinyhumansai/openhuman42k—~2.6kAutomated safety check: PassGPL-3.0
Systematic Code Refactoringluongnv89/claude-howto42k—~3kAutomated safety check: PassMIT
Codexskills-directory/skill-codex1.5k3 repos~1.8kAutomated safety check: PassMIT

Similar skills

  • Guidelines

    akash-network/node

    Behavioral guidelines to reduce common LLM coding mistakes. An agent skill from akash-network/node.

    1.1k GitHub starsUsed in 22 repos~577 tokens
    DevelopmentAuto-check passed
  • Component Refactoring

    langflow-ai/langflow

    Refactor high-complexity React components in Langflow frontend.

    156k GitHub stars~3.5k tokensUpdated today
    DevelopmentAuto-check passed
  • Migrate Core Code to Submodules

    tinyhumansai/openhuman

    Plans and carries out moving non-host-specific code and its tests from the OpenHuman core into vendored tiny submodule libraries, then releases the submodule and re-pins the host.

    42k GitHub stars~2.6k tokensUpdated today
    DevelopmentAuto-check passed
  • Systematic Code Refactoring

    luongnv89/claude-howto

    Guides refactoring in phases based on Martin Fowler's method: research, test coverage check, planning and small tested steps, with your approval at each phase.

    42k GitHub stars~3k tokensUpdated 7 days ago
    DevelopmentAuto-check passed
  • Codex

    skills-directory/skill-codex

    A skill your agent uses when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing

    1.5k GitHub starsUsed in 3 repos~1.8k tokens
    DevelopmentAuto-check passed
  • Ponytail

    DavidObando/gsharp

    Forces the laziest solution that actually works, simplest, shortest, most minimal.

    565 GitHub starsUsed in 8 repos~1.7k tokens
    DevelopmentAuto-check passed

More from oaustegard/claude-skills

All 69 skills in this repo
  • Bluesky Zeitgeist Sampler

    oaustegard/claude-skills

    Deprecated sampler that captures short windows of the Bluesky firehose, clusters trending terms and builds an HTML report; replaced by the browsing-bluesky skill.

    150 GitHub starsUsed in 1 repo~1.4k tokens
    Auto-check passed
  • Vega-Lite Interactive Charts

    oaustegard/claude-skills

    Builds interactive Vega-Lite charts from uploaded data: analyzes the fields, picks five to ten fitting chart types, and produces a React artifact with the data embedded inline.

    150 GitHub stars~2.1k tokensUpdated today
    Auto-check passed
  • Single-File HTML Composer

    oaustegard/claude-skills

    Builds self-contained single-file HTML pages such as reports, decks, postmortems, flowcharts and prototypes from a small spec using a bundled Python composer and templates.

    150 GitHub stars~3.2k tokensUpdated today
    Auto-check passed
  • Declauding

    oaustegard/claude-skills

    Rewrites model-sounding prose into plain technical writing and checks that every claim survives, for PR text, docs, commit messages and similar drafts.

    150 GitHub stars~5.2k tokensUpdated today
    Auto-check passed
  • Forecasting Reverso

    oaustegard/claude-skills

    Zero-shot univariate time series forecasting using the Reverso foundation model (NumPy/Numba CPU-only inference).

    150 GitHub starsUsed in 1 repo~1.5k tokens
    Auto-check passed
  • Preact Developer

    oaustegard/claude-skills

    Guides building standards-based Preact apps with native-first choices, HTM syntax, import maps and vendored ESM, from single-file demos to larger builds.

    150 GitHub stars~4.6k tokensUpdated today
    Auto-check passed

Categories

Questions about Iterating

What does Iterating do?

Multi-conversation methodology for iterative stateful work with context accumulation. Iterating is an agent skill from oaustegard/claude-skills. Multi-conversation methodology for iterative stateful work with context accumulation.

When should I use Iterating?

Iterating fits situations like: users request work that spans multiple sessions (research; feature development); need to build on past progress; explicitly mention iterative work.

How do I install Iterating in Claude Code?

Run `npx skills add oaustegard/claude-skills --skill iterating -a claude-code`. Or copy the skill folder (iterating in oaustegard/claude-skills) into .claude/skills/iterating in your project. Claude Code loads it when a task matches its description.

How do I install Iterating in Codex?

Run `npx skills add oaustegard/claude-skills --skill iterating -a codex`. Or copy the skill folder (iterating in oaustegard/claude-skills) into .agents/skills/iterating in your project. Codex loads it when a task matches its description.

Can I use Iterating 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 oaustegard/claude-skills --skill iterating -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iterating, .gemini/skills/iterating, .github/skills/iterating and .opencode/skills/iterating in your project.

What does Iterating need to run?

SKILL.md names no scripts, command-line tools or credentials: Iterating is instructions for the agent only.

Does Iterating 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 Iterating 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 Iterating use?

Iterating is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Iterating use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.

What are the alternatives to Iterating?

Skills that share tags, products or a category with Iterating: Guidelines (akash-network/node, 1.1k stars), Component Refactoring (langflow-ai/langflow, 156k stars), Migrate Core Code to Submodules (tinyhumansai/openhuman, 42k stars) and Systematic Code Refactoring (luongnv89/claude-howto, 42k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Iterating?

oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on October 8, 2026.

Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.