ccLoad Release Publisher
caidaoli/ccLoad
Publishes a ccLoad Beta or explicit stable release through a version-tag workflow, including commit, push, CI wait, GitHub Release and container image checks.
Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets.
Install Deployment Proof
$ npx skills add FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install FAIRY123456789/human-edge-agent-skills deployment-proof --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/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/deployment-proof .claude/skills/deployment-proof && 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 "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .claude/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proofType 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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install FAIRY123456789/human-edge-agent-skills deployment-proof --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/deployment-proof .agents/skills/deployment-proof && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .agents/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install FAIRY123456789/human-edge-agent-skills deployment-proof --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/deployment-proof .cursor/skills/deployment-proof && 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 "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .cursor/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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/FAIRY123456789/human-edge-agent-skills.git --path skills/deployment-proof--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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install FAIRY123456789/human-edge-agent-skills deployment-proof --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/deployment-proof .gemini/skills/deployment-proof && 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 "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .gemini/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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 FAIRY123456789/human-edge-agent-skills deployment-proofInstalls 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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/deployment-proof .github/skills/deployment-proof && 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 "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .github/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install FAIRY123456789/human-edge-agent-skills deployment-proof --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FAIRY123456789/human-edge-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/deployment-proof .opencode/skills/deployment-proof && 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 "deployment-proof" agent skill from https://github.com/FAIRY123456789/human-edge-agent-skills/tree/main/skills/deployment-proof into .opencode/skills/deployment-proof/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deployment-proof", 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
deployment-proof- GitHub stars
- 103
- Token cost
- ~980 tokens
- SKILL.md length
- 401 words
- Files
- 5 (incl. scripts, assets)
- Skills in repo
- 18
- Repo updated
- First seen
- Licence
- MIT
At a glance
Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets.
- Works in 5 steps: a concise GitHub case study; → three resume bullets using action,… → a 60–90 second interview story covering… → …
- Wants to demonstrate learning ability
- SKILL.md covers Build an evidence ledger first, Redact before writing, Tell the problem-to-proof story and Produce reusable career assets, plus 1 more section
- Runs Python scripts from its folder; calls python
What it does
Deployment Proof is an agent skill from FAIRY123456789/human-edge-agent-skills. Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets. Use after a software deployment, migration, recovery, or automation project when the user wants to demonstrate learning ability or impact without leaking host identities, credentials, private paths, customer data, or invented metrics. Do not publish or push unless the user explicitly asks.
Its SKILL.md is about 980 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and assets (for example `README.md`, `agents/openai.yaml` and `assets/case-study-template.md`).
It sits in DevOps & Cloud, covering Deployment and Git workflow. It works with GitHub. The repository describes itself as: 18 portable Agent Skills for voice-native AI, human judgment, microbets, social tact, writing, life systems, and safe deployment. The licence is MIT.
When your agent uses it
- Wants to demonstrate learning ability
- Impact without leaking host identities
- Invented metrics
Example prompts
- “/deployment-proof”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- a concise GitHub case study;
- three resume bullets using action, technical method, and demonstrated result;
- a 60–90 second interview story covering problem, investigation, reusable system, verification, and learning;
- a short launch post that invites feedback without claiming popularity;
- a list of evidence still needed for stronger quantified claims.
What it can do on your machine
Read from SKILL.md and the folder at commit 6ae0196. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
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
Deployment Proof loads about 980 tokens when it runs. Until then it costs about 123 tokens; SKILL.md has 401 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); the scripts in this folder are not scanned.
SKILL.md
The full file from FAIRY123456789/human-edge-agent-skills at commit 6ae0196, republished under its MIT licence (© FAIRY123456789). 401 words, ~980 tokens.
Download SKILL.mdSave it as
.claude/skills/deployment-proof/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- deployment-proof
- description
- Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets. Use after a software deployment, migration, recovery, or automation project when the user wants to demonstrate learning ability or impact without leaking host identities, credentials, private paths, customer data, or invented metrics. Do not publish or push unless the user explicitly asks.
- license
- MIT
- metadata.author
- Joy T <101039451+FAIRY123456789@users.noreply.github.com>
- metadata.tags
- deployment, case-study, redaction
Deployment Proof
Turn operational work into credible public evidence. Preserve what was difficult, what changed, and how success was verified; remove everything that identifies or grants access to the system.
Build an evidence ledger first
Collect only sources the user authorizes: deployment report, redacted logs, checksums, test output, Git changes and history, architecture notes, screenshots, and the original failure description. For each possible claim, record:
- claim;
- evidence source and date;
- baseline and result;
- verification method;
- confidentiality risk;
- confidence: confirmed, calculated, user-reported, or unknown.
Do not turn memory, confidence, or a successful health endpoint into a confirmed result. If the original process took “several days” but the automated run was not timed, say it became repeatable; do not invent a percentage or speedup.
Redact before writing
Remove public IPs, hostnames, SSH usernames, private application names and routes, account IDs, exact private filesystem paths, credentials, tokens, database URLs, personal and customer data, and private questions or AI prompts. Preserve reusable environment facts such as OS family, architecture, capacity class, runtime major and minor version, deployment topology, and failure class when safe.
Run:
python scripts/audit_public_report.py <draft-or-folder>A clean scan is necessary but not sufficient. Manually review screenshots, Git history, document metadata, filenames, QR codes, terminal prompts, and contextual identifiers that regex cannot understand.
Tell the problem-to-proof story
Copy assets/case-study-template.md into the output project and fill only sections supported by evidence. Lead with the outcome and audience pain:
Repeated manual deployment troubleshooting
-> reusable preflight, canary, promotion, and rollback workflow
-> verified release plus a public, redacted evidence trailShow a small architecture or gate sequence only when it makes the workflow easier to understand. Prefer a short verification table over a long command transcript.
Show full SKILL.md (144 more words)Show less
Produce reusable career assets
Create:
- a concise GitHub case study;
- three resume bullets using action, technical method, and demonstrated result;
- a 60–90 second interview story covering problem, investigation, reusable system, verification, and learning;
- a short launch post that invites feedback without claiming popularity;
- a list of evidence still needed for stronger quantified claims.
Describe the Skill as an engineering artifact, not merely “using AI.” Emphasize problem discovery, workflow design, parameterization, safety boundaries, deterministic tooling, verification, iteration, and public documentation.
Quality gate
Before delivery, confirm:
- every number has a source;
- every success claim names its verification;
- user-reported timing is labeled as such;
- the draft contains no secrets or private identifiers;
- compatibility scope matches what was actually tested;
- installation and first-use instructions are copyable;
- limitations and untested paths are visible;
- no publish, push, post, or external message occurred without explicit authorization.
© FAIRY123456789, 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 4 other files (scripts, assets) in skills/deployment-proof of FAIRY123456789/human-edge-agent-skills.
- SKILL.md
- README.md
- agents/openai.yaml
- assets/case-study-template.md
- scripts/audit_public_report.py
Open the folder on GitHubat commit 6ae0196
Compare with similar skills
Deployment Proof 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 |
|---|---|---|---|---|---|---|
| Deployment Proof this skillFAIRY123456789/human-edge-agent-skills | 103 | — | ~980 | Automated safety check: Pass | MIT | |
| ccLoad Release Publishercaidaoli/ccLoad | 419 | — | ~887 | Automated safety check: Pass | MIT | |
| ClawRouter Release ChecklistBlockRunAI/ClawRouter | 6.6k | — | ~1.4k | Automated safety check: Pass | MIT | |
| AI News RadarLearnPrompt/ai-news-radar | 1.8k | — | ~2.5k | Automated safety check: Notes | MIT | |
| Reflexo ReleaseMyriad-Dreamin/typst.ts | 1.2k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| GreptimeDB Release RunbookGreptimeTeam/greptimedb | 6.7k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about Deployment Proof
What does Deployment Proof do?
Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets. Deployment Proof is an agent skill from FAIRY123456789/human-edge-agent-skills. Convert deployment logs, validation reports, Git history, and comparison notes into a redacted GitHub case study, portfolio entry, interview story, and evidence-backed resume bullets.
When should I use Deployment Proof?
Deployment Proof fits situations like: wants to demonstrate learning ability; impact without leaking host identities; invented metrics.
How do I install Deployment Proof in Claude Code?
Run `npx skills add FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a claude-code`. Or copy the skill folder (skills/deployment-proof in FAIRY123456789/human-edge-agent-skills) into .claude/skills/deployment-proof in your project. Claude Code loads it when a task matches its description.
How do I install Deployment Proof in Codex?
Run `npx skills add FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a codex`. Or copy the skill folder (skills/deployment-proof in FAIRY123456789/human-edge-agent-skills) into .agents/skills/deployment-proof in your project. Codex loads it when a task matches its description.
Can I use Deployment Proof 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 FAIRY123456789/human-edge-agent-skills --skill deployment-proof -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deployment-proof, .gemini/skills/deployment-proof, .github/skills/deployment-proof and .opencode/skills/deployment-proof in your project.
What does Deployment Proof need to run?
Going by SKILL.md and its folder, Deployment Proof needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Deployment Proof 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 Deployment Proof 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Deployment Proof use?
Deployment Proof is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Deployment Proof use?
About 980 tokens (SKILL.md is roughly 3.9k 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 Deployment Proof?
Skills that share tags, products or a category with Deployment Proof: ccLoad Release Publisher (caidaoli/ccLoad, 419 stars), ClawRouter Release Checklist (BlockRunAI/ClawRouter, 6.6k stars), AI News Radar (LearnPrompt/ai-news-radar, 1.8k stars) and Reflexo Release (Myriad-Dreamin/typst.ts, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deployment Proof?
FAIRY123456789 (a GitHub user) maintains it in FAIRY123456789/human-edge-agent-skills, which has 103 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on September 30, 2026.
Source: FAIRY123456789/human-edge-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.