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Author SHA1 Message Date
Space-Banane a3ba7b3176 Add Python copy-script installer
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2026-06-03 14:19:57 +02:00
space 30166f9fa2 Updated Spec & Skills
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2026-06-02 18:21:38 +02:00
space f35f7ebd93 Added more words to cspell 2026-06-02 18:02:17 +02:00
space a231966dd3 Added an Agents.md
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2026-06-02 18:00:57 +02:00
space b51798905f New spellchecker
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2026-06-02 17:59:14 +02:00
11 changed files with 264 additions and 10 deletions
+4 -4
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@@ -17,8 +17,8 @@ jobs:
- name: Check out repository
uses: actions/checkout@v4
- name: Install codespell
run: python -m pip install --upgrade codespell --break-system-packages
- name: Check Markdown spelling
run: codespell $(git ls-files '**/*.md')
uses: streetsidesoftware/cspell-action@v6
with:
config: cspell.json
files: "**/*.md"
+24
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@@ -0,0 +1,24 @@
# AGENTS.md
## Purpose
This repository packages the `idea-evaluator` skill for multiple agent ecosystems.
Treat the root files as the canonical project guidance:
- `Intent.md` is the behavior spec for the skill.
- `README.md` explains the repo layout at a high level.
- `cspell.json` defines the spellcheck vocabulary used by CI.
## Working Rules
- Read `Intent.md` and `README.md` before making repo-wide changes.
- Keep the three package folders aligned when a shared description changes.
- Keep prose concise and consistent across `codex/`, `claude/`, and `openclaw/`.
- When adding new markdown wording or project terms, update `cspell.json` if CI should accept them.
- Preserve intentional misspellings only when they are part of a test or a deliberate example.
- Prefer `apply_patch` for edits and keep changes minimal.
## Validation
- Markdown files are checked in CI with `cspell`.
- Make sure new or edited `.md` files pass spellcheck before you consider the work done.
+2 -1
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@@ -35,6 +35,8 @@ The skill exists to answer:
The evaluation must happen in 3 stages.
Before moving to the next stage, wait until every agent in the current stage has finished its research and returned its output.
### Stage 1: Broad Scan
Launch 5 subagents.
@@ -110,4 +112,3 @@ The skill is successful if it can:
- support strong ideas with real reasoning,
- surface useful market and execution risks,
- and help the user decide whether the idea deserves an MVP.
+6
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@@ -8,6 +8,7 @@ This repository packages the same `idea-evaluator` concept for three different a
- `codex/idea-evaluator`: Codex-formatted package
- `claude/idea-evaluator`: Claude Code-formatted package
- `openclaw/idea-evaluator`: OpenClaw-formatted package
- `copy-script/`: Python installer and its README
## What It Does
@@ -23,6 +24,11 @@ It is designed to:
- `Intent.md` is the canonical brief for the skill
- Each package folder contains a `SKILL.md` plus a short README for that ecosystem
- `copy-script/README.md` explains the installer and its options
## Installation
Run the Python installer in `copy-script/` to copy the package folders into the matching skills directories under your home folder.
## License
+2 -1
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@@ -20,6 +20,8 @@ Treat the task like a structured decision engine:
Run the evaluation in 3 stages.
Before moving to the next stage, wait until every agent in the current stage has finished its research and returned its output.
### Stage 1: Broad Scan
Launch 5 subagents.
@@ -87,4 +89,3 @@ Include:
- positives
- negatives
- MVP question
+2 -1
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@@ -20,6 +20,8 @@ Treat the task like a structured decision engine:
Run the evaluation in 3 stages.
Before moving to the next stage, wait until every agent in the current stage has finished its research and returned its output.
### Stage 1: Broad Scan
Launch 5 subagents.
@@ -87,4 +89,3 @@ Include:
- positives
- negatives
- MVP question
+43
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@@ -0,0 +1,43 @@
# Copy Script
This folder contains the Python installer for the `idea-evaluator` skill packages.
## What It Does
The script copies each ecosystem package into the matching skills directory in your home folder:
- `codex/idea-evaluator` -> `~/.codex/skills/idea-evaluator`
- `claude/idea-evaluator` -> `~/.claude/skills/idea-evaluator`
- `openclaw/idea-evaluator` -> `~/.openclaw/skills/idea-evaluator`
## Interactive Mode
Run the script with no flags in a terminal to pick ecosystems interactively.
It will:
- show the available ecosystems,
- let you choose one or more,
- and ask before overwriting existing installs.
## CLI Mode
Use flags when you want a non-interactive run.
Examples:
```bash
python copy-script/install-skills.py --all
python copy-script/install-skills.py --ecosystems codex openclaw
python copy-script/install-skills.py --all --dry-run
python copy-script/install-skills.py --all --force
```
## Options
- `--all`: install into every supported ecosystem
- `--ecosystems`: install into selected ecosystems only
- `--repo-root`: point the script at a different repository root
- `--home`: point the script at a different home directory
- `--dry-run`: print actions without copying files
- `--force`: skip overwrite confirmation
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@@ -0,0 +1,155 @@
from __future__ import annotations
import argparse
import shutil
import sys
from pathlib import Path
ECOSYSTEMS = {
"codex": ("codex", ".codex"),
"claude": ("claude", ".claude"),
"openclaw": ("openclaw", ".openclaw"),
}
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(
description="Copy the idea-evaluator skill packages into local skills directories."
)
parser.add_argument(
"--ecosystems",
nargs="+",
choices=sorted(ECOSYSTEMS),
help="One or more ecosystems to install into. Omit for interactive mode.",
)
parser.add_argument(
"--all",
action="store_true",
help="Install into all supported ecosystems.",
)
parser.add_argument(
"--repo-root",
type=Path,
default=Path(__file__).resolve().parent.parent,
help="Path to the repository root. Defaults to the parent of copy-script/.",
)
parser.add_argument(
"--home",
type=Path,
default=Path.home(),
help="Home directory that contains the target skills folders.",
)
parser.add_argument(
"--dry-run",
action="store_true",
help="Show what would be copied without writing anything.",
)
parser.add_argument(
"--force",
action="store_true",
help="Overwrite existing installations without prompting.",
)
return parser
def prompt_ecosystems() -> list[str]:
options = list(ECOSYSTEMS)
print("Select ecosystems to install:")
for index, name in enumerate(options, start=1):
print(f" {index}. {name}")
print(" a. all")
choice = input("Enter numbers or names separated by commas [a]: ").strip().lower()
if not choice or choice == "a" or choice == "all":
return options
selected: list[str] = []
for raw_item in choice.split(","):
item = raw_item.strip()
if not item:
continue
if item.isdigit():
index = int(item) - 1
if index < 0 or index >= len(options):
raise SystemExit(f"Invalid ecosystem number: {item}")
selected.append(options[index])
continue
if item not in ECOSYSTEMS:
raise SystemExit(f"Unknown ecosystem: {item}")
selected.append(item)
if not selected:
raise SystemExit("No ecosystems selected.")
return list(dict.fromkeys(selected))
def prompt_confirmation(message: str) -> bool:
choice = input(f"{message} [y/N]: ").strip().lower()
return choice in {"y", "yes"}
def resolve_targets(args: argparse.Namespace) -> list[str]:
if args.all:
return list(ECOSYSTEMS)
if args.ecosystems:
return list(dict.fromkeys(args.ecosystems))
if sys.stdin.isatty():
return prompt_ecosystems()
raise SystemExit("Specify --all or --ecosystems when running non-interactively.")
def install_skill(source: Path, destination_root: Path, dry_run: bool) -> Path:
destination = destination_root / source.name
if dry_run:
print(f"Would copy {source} -> {destination}")
return destination
destination_root.mkdir(parents=True, exist_ok=True)
if destination.exists():
if destination.is_dir():
shutil.rmtree(destination)
else:
destination.unlink()
shutil.copytree(source, destination)
print(f"Copied {source} -> {destination}")
return destination
def main() -> None:
parser = build_parser()
args = parser.parse_args()
repo_root = args.repo_root.resolve()
home = args.home.expanduser().resolve()
selected = resolve_targets(args)
jobs = []
for ecosystem in selected:
source_dirname, destination_dirname = ECOSYSTEMS[ecosystem]
source = repo_root / source_dirname / "idea-evaluator"
destination_root = home / destination_dirname / "skills"
jobs.append((ecosystem, source, destination_root))
if not args.force and not args.dry_run:
destinations = [destination_root / "idea-evaluator" for _, _, destination_root in jobs]
existing = [path for path in destinations if path.exists()]
if existing:
print("Existing installations found:")
for path in existing:
print(f" {path}")
if not sys.stdin.isatty() or not prompt_confirmation("Overwrite them"):
raise SystemExit("Cancelled.")
for _, source, destination_root in jobs:
install_skill(source, destination_root, args.dry_run)
if __name__ == "__main__":
main()
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@@ -0,0 +1,23 @@
{
"version": "0.2",
"language": "en",
"words": [
"AGENTS",
"Codex",
"Claude",
"Gitea",
"MVP",
"OpenClaw",
"README",
"copy-script",
"apply_patch",
"cspell",
"idea-evaluator",
"frontmatter",
"subagents",
"hyphen-case"
],
"ignorePaths": [
"LICENSE"
]
}
+1 -2
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@@ -6,10 +6,9 @@ This folder contains the OpenClaw version of `idea-evaluator`.
- OpenClaw loads skills from `SKILL.md` files with YAML frontmatter.
- The skill name lives in frontmatter and should stay lowercase hyphen-case.
- The body stas concise because it is the operating playbook once the skill triggers.
- The body stays concise because it is the operating playbook once the skill triggers.
## Source
- `Intent.md` in the repo root
- OpenClaw skill loading and frontmatter rules
+2 -1
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@@ -20,6 +20,8 @@ Treat the task like a structured decision engine:
Run the evaluation in 3 stages.
Before moving to the next stage, wait until every agent in the current stage has finished its research and returned its output.
### Stage 1: Broad Scan
Launch 5 subagents.
@@ -87,4 +89,3 @@ Include:
- positives
- negatives
- MVP question