Deepsec Documentation Guide
vercel-labs/deepsec
Points the agent at deepsec's own docs to answer questions about initializing, configuring, resuming, scanning with and extending the vulnerability scanner.
Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live…
Install Analyze Cloud Control Plane Evidence
$ npx skills add cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install cyberful/cyberful analyze-cloud-control-plane-evidence --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/cyberful/cyberful.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .claude/skills/analyze-cloud-control-plane-evidence && 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 "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .claude/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidenceType 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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install cyberful/cyberful analyze-cloud-control-plane-evidence --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/cyberful/cyberful.git skills-src && mkdir -p .agents/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .agents/skills/analyze-cloud-control-plane-evidence && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .agents/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install cyberful/cyberful analyze-cloud-control-plane-evidence --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/cyberful/cyberful.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .cursor/skills/analyze-cloud-control-plane-evidence && 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 "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .cursor/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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/cyberful/cyberful.git --path cyberful/builtin/skills/analyze-cloud-control-plane-evidence--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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install cyberful/cyberful analyze-cloud-control-plane-evidence --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/cyberful/cyberful.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .gemini/skills/analyze-cloud-control-plane-evidence && 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 "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .gemini/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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 cyberful/cyberful analyze-cloud-control-plane-evidenceInstalls 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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/cyberful/cyberful.git skills-src && mkdir -p .github/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .github/skills/analyze-cloud-control-plane-evidence && 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 "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .github/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install cyberful/cyberful analyze-cloud-control-plane-evidence --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/cyberful/cyberful.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/cyberful/builtin/skills/analyze-cloud-control-plane-evidence .opencode/skills/analyze-cloud-control-plane-evidence && 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 "analyze-cloud-control-plane-evidence" agent skill from https://github.com/cyberful/cyberful/tree/main/cyberful/builtin/skills/analyze-cloud-control-plane-evidence into .opencode/skills/analyze-cloud-control-plane-evidence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-cloud-control-plane-evidence", 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
analyze-cloud-control-plane-evidence- GitHub stars
- 135
- Token cost
- ~471 tokens
- SKILL.md length
- 129 words
- Files
- 10 (incl. scripts, references, assets)
- Skills in repo
- 85
- Repo updated
- First seen
- Licence
- AGPL-3.0
At a glance
Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live…
- Security work in your project
- Runs Python scripts from its folder
What it does
Analyze Cloud Control Plane Evidence is an agent skill from cyberful/cyberful. Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live provider.
Its SKILL.md is about 470 tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `assets/cloud-control-plane-evidence.schema.json` and `assets/cloud-control-plane-input.example.json`).
It sits in Security. The repository describes itself as: Cyberful is an open-source AI Red Team for discovering, exploiting, verifying, and remediating vulnerabilities. The licence is AGPL-3.0.
When your agent uses it
- Security work in your project
Example prompts
- “/analyze-cloud-control-plane-evidence”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit ec598a6. 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 2 files in scripts/ (Python), which the agent can run.
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
Analyze Cloud Control Plane Evidence loads about 471 tokens when it runs, and up to ~680 if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 129 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 cyberful/cyberful at commit ec598a6, republished under its AGPL-3.0 licence (© cyberful). 129 words, ~471 tokens.
Download SKILL.mdSave it as
.claude/skills/analyze-cloud-control-plane-evidence/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- analyze-cloud-control-plane-evidence
- description
- Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live provider.
- metadata.domain
- cloud-security
- metadata.subdomain
- control-plane-evidence
- metadata.triggers
- analyze cloud control plane evidence, compare cloud snapshots, cloud resource drift evidence, reconcile IAM observations, offline cloud posture analysis
- metadata.tags
- cloud, control-plane, snapshots, drift, IAM, offline-analysis
Analyze Cloud Control-Plane Evidence
Reconcile normalized snapshots as evidence, not as a live provider truth source. Preserve provider, account or project, capture time, collector identity, scope limitations, and raw resource identity.
Stage scripts/analyze_cloud_control_plane.py, its manifest, and the example. The analyzer is offline, reads only confined regular JSON snapshots, starts no child process, and writes deterministic bounded drift evidence under the output schema.
Read control-plane-evidence-method.md before treating an absent resource or changed control as drift. A collector can omit fields it lacked permission to observe.
Interpret deltas
Separate added, removed, and changed resources. For changes, compare public exposure, principals, policy digest, encryption, logging, and lifecycle state field by field. Escalate the mechanism to the relevant cloud audit or identity specialist; this skill does not infer exploitability or make live calls.
© cyberful, AGPL-3.0. 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 9 other files (scripts, references, assets) in cyberful/builtin/skills/analyze-cloud-control-plane-evidence of cyberful/cyberful.
- SKILL.md
- agents/openai.yaml
- assets/cloud-control-plane-evidence.schema.json
- assets/cloud-control-plane-input.example.json
- assets/cloud-control-plane-input.schema.json
- assets/cloud-control-plane-snapshot.schema.json
- references/control-plane-evidence-method.md
- scripts/analyze_cloud_control_plane.py
- scripts/manifest.json
- tests/test_analyze_cloud_control_plane.py
Open the folder on GitHubat commit ec598a6
Compare with similar skills
Analyze Cloud Control Plane Evidence 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 |
|---|---|---|---|---|---|---|
| Analyze Cloud Control Plane Evidence this skillcyberful/cyberful | 135 | — | ~471 | Automated safety check: Pass | AGPL-3.0 | |
| Deepsec Documentation Guidevercel-labs/deepsec | 8.1k | — | ~956 | Automated safety check: Pass | Apache-2.0 | |
| Skill Scannergetsentry/skills | 1k | 4 repos | ~2.5k | Automated safety check: Warn | Apache-2.0 | |
| Serenity Aleabitoreddityan-labs/serenity-aleabitoreddit | 481 | 1 repos | ~3.3k | Automated safety check: Pass | None | |
| Security Alert Triageelastic/agent-skills | 592 | 1 repos | ~3.5k | Automated safety check: Notes | Apache-2.0 | |
| Shiro Attack CLISummerSec/ShiroAttack2 | 2.6k | — | ~945 | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Analyze Cloud Control Plane Evidence
What does Analyze Cloud Control Plane Evidence do?
Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live…. Analyze Cloud Control Plane Evidence is an agent skill from cyberful/cyberful. Deterministically reconcile bounded offline cloud control-plane snapshots to expose resource, public-access, principal, policy, encryption, logging, and lifecycle drift without querying a live provider.
When should I use Analyze Cloud Control Plane Evidence?
Analyze Cloud Control Plane Evidence fits situations like: security work in your project.
How do I install Analyze Cloud Control Plane Evidence in Claude Code?
Run `npx skills add cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a claude-code`. Or copy the skill folder (cyberful/builtin/skills/analyze-cloud-control-plane-evidence in cyberful/cyberful) into .claude/skills/analyze-cloud-control-plane-evidence in your project. Claude Code loads it when a task matches its description.
How do I install Analyze Cloud Control Plane Evidence in Codex?
Run `npx skills add cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a codex`. Or copy the skill folder (cyberful/builtin/skills/analyze-cloud-control-plane-evidence in cyberful/cyberful) into .agents/skills/analyze-cloud-control-plane-evidence in your project. Codex loads it when a task matches its description.
Can I use Analyze Cloud Control Plane Evidence 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 cyberful/cyberful --skill analyze-cloud-control-plane-evidence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-cloud-control-plane-evidence, .gemini/skills/analyze-cloud-control-plane-evidence, .github/skills/analyze-cloud-control-plane-evidence and .opencode/skills/analyze-cloud-control-plane-evidence in your project.
What does Analyze Cloud Control Plane Evidence need to run?
Going by SKILL.md and its folder, Analyze Cloud Control Plane Evidence needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Analyze Cloud Control Plane Evidence 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 Analyze Cloud Control Plane Evidence 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 Analyze Cloud Control Plane Evidence use?
Analyze Cloud Control Plane Evidence is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Analyze Cloud Control Plane Evidence use?
About 471 tokens (SKILL.md is roughly 1.9k 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 209 tokens, read only when the agent opens those files.
What are the alternatives to Analyze Cloud Control Plane Evidence?
Skills that share tags, products or a category with Analyze Cloud Control Plane Evidence: Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Skill Scanner (getsentry/skills, 1k stars), Serenity Aleabitoreddit (yan-labs/serenity-aleabitoreddit, 481 stars) and Security Alert Triage (elastic/agent-skills, 592 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Analyze Cloud Control Plane Evidence?
cyberful (a GitHub organization) maintains it in cyberful/cyberful, which has 135 GitHub stars. The repository holds 85 skills in this directory. The repository was last updated on August 24, 2026.
Source: cyberful/cyberful on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.