Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed.
Install Incremental Analysis
$ npx skills add prime-radiant-inc/greenfield --skill incremental-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install prime-radiant-inc/greenfield incremental-analysis --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/greenfield.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/incremental-analysis .claude/skills/incremental-analysis && 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 "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .claude/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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/greenfield/tree/main/skills/incremental-analysisType 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/greenfield --skill incremental-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install prime-radiant-inc/greenfield incremental-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/greenfield.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/incremental-analysis .agents/skills/incremental-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .agents/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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/greenfield --skill incremental-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install prime-radiant-inc/greenfield incremental-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/greenfield.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/incremental-analysis .cursor/skills/incremental-analysis && 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 "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .cursor/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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/greenfield.git --path skills/incremental-analysis--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/greenfield --skill incremental-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install prime-radiant-inc/greenfield incremental-analysis --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/greenfield.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/incremental-analysis .gemini/skills/incremental-analysis && 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 "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .gemini/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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/greenfield incremental-analysisInstalls 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/greenfield --skill incremental-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/prime-radiant-inc/greenfield.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/incremental-analysis .github/skills/incremental-analysis && 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 "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .github/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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/greenfield --skill incremental-analysis -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/greenfield incremental-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/prime-radiant-inc/greenfield.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/incremental-analysis .opencode/skills/incremental-analysis && 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 "incremental-analysis" agent skill from https://github.com/prime-radiant-inc/greenfield/tree/main/skills/incremental-analysis into .opencode/skills/incremental-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "incremental-analysis", 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
incremental-analysis- GitHub stars
- 292
- Token cost
- ~2.2k tokens
- SKILL.md length
- 809 words
- Files
- 1
- Skills in repo
- 21
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed.
- Works in 6 steps: Fresh Discovery → Diff Against Existing Specs → Classify Specs → …
- Development work in your project
- SKILL.md covers When to Use, High Water Mark Metadata, Incremental Detection and Incremental Flow, plus 2 more sections
- Calls git
What it does
Incremental Analysis is an agent skill from prime-radiant-inc/greenfield. Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed. Activates automatically when /analyze finds an existing workspace.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development. It works with Git. The repository describes itself as: A Claude Code plugin that reverse-engineers clean behavioral specs, test vectors, and acceptance criteria from any codebase, producing a provenance trail so a fresh team can… The licence is Apache-2.0.
When your agent uses it
- Development work in your project
Example prompts
- “/incremental-analysis”
Workflow steps
6 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 6e6d4b4. 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
Shell commands in SKILL.md call:
git
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
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
Incremental Analysis loads about 2.2k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 809 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/greenfield at commit 6e6d4b4, republished under its Apache-2.0 licence (© prime-radiant-inc). 809 words, ~2,164 tokens.
Download SKILL.mdSave it as
.claude/skills/incremental-analysis/SKILL.md (or your agent's skills folder).- name
- incremental-analysis
- description
- Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed. Activates automatically when /analyze finds an existing workspace.
Incremental Analysis
When a workspace already exists for a target, avoid re-analyzing unchanged sources. Diff the current state against what was previously analyzed and re-analyze only what's stale.
When to Use
This skill activates automatically when /analyze is invoked and a workspace directory already exists at the target path. No --follow flag needed. If the workspace has a .git directory, this is an incremental run. Otherwise, it's a fresh analysis.
Note: --follow is for continuing an interrupted analysis within a single run. Incremental analysis is for subsequent runs against an evolved codebase.
High Water Mark Metadata
Each raw specs tracks the sources it was derived from in YAML frontmatter. This metadata is the basis for incremental diffing.
---
spec_id: SPEC-SESSION-001
derived_from:
- path: workspace/raw/source/analysis/session-module.md
source_ref: a1b2c3d # git SHA of original source file, if available
file_hash: sha256:deadbeef1234 # sha256 of source artifact at analysis time
- path: workspace/public/docs/session-api.md
fetched_at: 2026-04-13T10:00:00Z
url: https://docs.example.com/sessions
- path: workspace/raw/test-evidence/e2e-session-flow.md
file_hash: sha256:cafebabe5678
analyzed_at: 2026-04-13T14:30:00Z
greenfield_version: "2.0"
---Derived From Entry Types
Each entry in derived_from uses the fields appropriate to its source type:
| Source Type | Required Fields | Optional Fields |
|---|---|---|
| Source code artifact | path, file_hash | source_ref (git SHA) |
| Web-fetched doc | path, url, fetched_at | file_hash |
| Runtime observation | path, file_hash | timestamp in fetched_at |
| Git history | path, source_ref | file_hash |
| Test evidence | path, file_hash | -- |
Writing High Water Marks
When writing or updating a raw spec, always include derived_from metadata:
- For source code artifacts: include the git SHA of the original source file (if available) and the sha256 hash of the analysis artifact
- For web-fetched docs: include the fetch timestamp and URL
- For runtime observations: include the observation timestamp
- For test evidence: include the file hash of the evidence artifact
Incremental Detection
When /analyze is invoked, before workspace initialization:
WORKSPACE="${WORKSPACE_ARG:-./analysis-workspace}"
if [ -d "$WORKSPACE/.git" ]; then
echo "Existing workspace detected at $WORKSPACE"
echo "Running incremental analysis..."
# Proceed with incremental flow (this skill)
else
echo "No existing workspace. Running fresh analysis..."
# Proceed with fresh workspace initialization (standard /analyze flow)
fiTo force a fresh analysis, delete the workspace directory.
Incremental Flow
Step 1: Fresh Discovery
Run the discovery/inventory phase to produce a new inventory manifest. This is always fresh -- the available sources may have changed since the last run. New files may exist, old files may have been deleted, documentation may have been updated.
The output is a complete inventory of what sources are available NOW, independent of what was analyzed before.
Step 2: Diff Against Existing Specs
For each existing raw specs, check its derived_from metadata against current state:
# For each source with a git ref:
current_sha=$(git -C "$SOURCE_REPO" log -1 --format="%H" -- "$SOURCE_FILE")
# Compare against source_ref in derived_from
# For each source with a file hash:
current_hash=$(sha256sum "$ARTIFACT_PATH" | cut -d' ' -f1)
# Compare against file_hash in derived_from
# For web sources:
# Check if content has changed (HTTP ETag/Last-Modified, or re-fetch and diff)Step 3: Classify Specs
Each existing spec gets exactly one classification:
| Classification | Criteria | Action |
|---|---|---|
| Unchanged | All derived_from sources match current state (same hash/SHA) | Carry forward as-is |
| Stale | One or more derived_from sources have changed | Queue for re-analysis |
| Orphaned | A derived_from source no longer exists | Queue for re-analysis (may result in spec removal) |
| New | Discovery found sources with no corresponding spec | Queue for fresh analysis |
Write the classification results to the workspace before proceeding:
workspace/raw/incremental/
classification.md # Summary: N unchanged, N stale, N orphaned, N new
unchanged.txt # List of spec IDs carried forward
stale.txt # List of spec IDs queued for re-analysis, with changed sources
orphaned.txt # List of spec IDs whose sources no longer exist
new.txt # List of new sources needing analysisStep 4: Re-Analyze
For stale specs: dispatch the appropriate Layer 1-3 agents. The analysis agents write updated specs that replace the stale versions. The derived_from metadata is updated with current hashes/SHAs.
For new sources: dispatch fresh Layer 1-3 analysis. Produces new spec files with derived_from metadata.
For orphaned specs: if the source was removed (feature deleted), remove the spec. If the source was renamed or moved, the discovery agent should detect the new location and classify it as "new" instead. When uncertain, flag for manual review rather than silently deleting.
For unchanged specs: no action. Carry forward as-is.
Show full SKILL.md (305 more words)Show less
Step 5: Re-Validate (Gates 1-2)
Run Gates 1-2 on the full set (carried forward + updated + new). Cross-module interactions may have changed even if a spec's direct sources didn't. A change in one module can create contradictions with an unchanged spec in another module.
Gate failures during incremental runs follow the same remediation loop as fresh runs (up to 3 attempts).
Step 6: Re-Sanitize and Audit (Layers 5-7)
Re-run Layers 5-7 on everything -- not just the changed specs. This is required because:
- Layer 5 (Sanitization) is a rewrite pass. The sanitizer's understanding of the whole system may have changed with new/updated specs. A carried-forward spec that was properly sanitized last run may need different treatment now that adjacent specs have changed.
- Layer 6 (Second-Pass Review) must see the complete output. Partial audits miss cross-file leakage.
- Layer 7 (Fidelity Check) must validate the complete raw-to-clean mapping.
Sanitization is cheap relative to Layer 1-3 analysis. The sanitization discipline requires a fresh rewrite pass regardless.
Workspace Metadata Update
After incremental analysis completes, append to the run_history array in workspace.json:
{
"run_history": [
{
"run_id": "001",
"started_at": "2026-04-13T10:00:00Z",
"completed_at": "2026-04-13T14:30:00Z",
"type": "fresh",
"specs_analyzed": 24,
"specs_carried_forward": 0,
"source_high_water": "a1b2c3d"
},
{
"run_id": "002",
"started_at": "2026-04-20T09:00:00Z",
"completed_at": "2026-04-20T10:15:00Z",
"type": "incremental",
"specs_analyzed": 3,
"specs_carried_forward": 21,
"specs_orphaned": 0,
"source_high_water": "d4e5f6a"
}
]
}Run History Fields
| Field | Type | Description |
|---|---|---|
run_id | string | Sequential identifier (zero-padded) |
started_at | ISO 8601 | When the run began |
completed_at | ISO 8601 | When the run finished |
type | enum | fresh or incremental |
specs_analyzed | integer | Specs that went through Layer 1-3 analysis |
specs_carried_forward | integer | Unchanged specs carried forward (0 for fresh runs) |
specs_orphaned | integer | Specs removed because sources no longer exist |
source_high_water | string | Git SHA of the source repo HEAD at analysis time |
Relationship to Other Skills
- analysis-pipeline: Master methodology; incremental analysis modifies which specs enter the pipeline, not the pipeline itself
- source-analysis: Layer 1 source analysis; dispatched for stale and new specs during incremental runs
- validation-methodology: Gates 1-2 run on the full set regardless of incremental vs fresh
- spec-sanitization: Layers 5-7 always run on everything; incremental savings come from Layers 1-3 only
© 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
Just SKILL.md in skills/incremental-analysis of prime-radiant-inc/greenfield.
Open the folder on GitHubat commit 6e6d4b4
Compare with similar skills
Incremental Analysis 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 |
|---|---|---|---|---|---|---|
| Incremental Analysis this skillprime-radiant-inc/greenfield | 292 | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Code Design Rationale Investigatorcursor/plugins | 11k | 9 repos | ~2.6k | Automated safety check: Pass | None | |
| Contributor-First PR MergeHKUDS/OpenHarness | 16k | 1 repos | ~847 | Automated safety check: Pass | MIT | |
| Finishing A Development Branchfarm-fe/farm | 5.6k | 34 repos | ~1.8k | Automated safety check: Pass | MIT |
Similar skills
Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
- Official
Code Design Rationale Investigator
cursor/plugins
Digs into why code is shaped the way it is by checking git history, pull requests and connected tools in parallel, then reporting a cited read on the tradeoffs.
Contributor-First PR Merge
HKUDS/OpenHarness
Merges external GitHub pull requests while keeping the original author credited, and fixes conflicts after the merge instead of rewriting the contribution.
Finishing A Development Branch
farm-fe/farm
A skill your agent uses when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for…
Migrate Internal Package into Ghost
TryGhost/Ghost
Moves a package from another TryGhost repository into Ghost as an internal workspace package while keeping its Git history, with checkpoints for the steps that need an administrator.
More from prime-radiant-inc/greenfield
All 21 skills in this repoReverse Engineering Analysis Pipeline
prime-radiant-inc/greenfield
Master methodology for reverse-engineering a codebase into behavioral specs with cited evidence, reading every line across source, binaries, docs, runtime and git history.
Community Intelligence Research
prime-radiant-inc/greenfield
Mines tutorials, forums, reviews, issues and changelogs for observed product behavior, using six search channels and consensus analysis.
Containerized Target Execution
prime-radiant-inc/greenfield
Runs untrusted analysis targets inside Docker or Podman containers with memory, CPU and process limits, covering image builds, lifecycle, command execution and cleanup.
API Contract Detection
prime-radiant-inc/greenfield
Finds OpenAPI, GraphQL, Protobuf and JSON Schema files in a codebase and extracts behavioral claims from them as part of a reverse-engineering workflow.
Documentation Research Methodology
prime-radiant-inc/greenfield
Method for extracting behavioral specifications from a product's public documentation: tiered search order, claim extraction rules, output structure, stop criteria and gap analysis.
Ecosystem Analysis
prime-radiant-inc/greenfield
Layer 1 skill for SDK and ecosystem analysis. An agent skill from prime-radiant-inc/greenfield.
Related
Works with
Categories
Questions about Incremental Analysis
What does Incremental Analysis do?
Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed. Incremental Analysis is an agent skill from prime-radiant-inc/greenfield. Detect existing workspace, diff current sources against high water mark metadata, classify specs as unchanged/stale/orphaned/new, re-analyze only what changed.
When should I use Incremental Analysis?
Incremental Analysis fits situations like: development work in your project.
How do I install Incremental Analysis in Claude Code?
Run `npx skills add prime-radiant-inc/greenfield --skill incremental-analysis -a claude-code`. Or copy the skill folder (skills/incremental-analysis in prime-radiant-inc/greenfield) into .claude/skills/incremental-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Incremental Analysis in Codex?
Run `npx skills add prime-radiant-inc/greenfield --skill incremental-analysis -a codex`. Or copy the skill folder (skills/incremental-analysis in prime-radiant-inc/greenfield) into .agents/skills/incremental-analysis in your project. Codex loads it when a task matches its description.
Can I use Incremental Analysis 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/greenfield --skill incremental-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/incremental-analysis, .gemini/skills/incremental-analysis, .github/skills/incremental-analysis and .opencode/skills/incremental-analysis in your project.
What does Incremental Analysis need to run?
Going by SKILL.md and its folder, Incremental Analysis needs the command-line tools its instructions call (git).
Does Incremental Analysis access the network?
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Incremental Analysis 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 Incremental Analysis use?
Incremental Analysis 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 Incremental Analysis use?
About 2.2k tokens (SKILL.md is roughly 8.7k 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 Incremental Analysis?
Skills that share tags, products or a category with Incremental Analysis: Finishing a Development Branch (obra/superpowers, 297k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Code Design Rationale Investigator (cursor/plugins, 11k stars) and Contributor-First PR Merge (HKUDS/OpenHarness, 16k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Incremental Analysis?
prime-radiant-inc (a GitHub organization) maintains it in prime-radiant-inc/greenfield, which has 292 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on August 6, 2026.
Source: prime-radiant-inc/greenfield on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.