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.
A skill your agent uses when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change.
$ npx skills add vlinx-io/VelaTerm --skill finding-discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vlinx-io/VelaTerm finding-discovery --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/vlinx-io/VelaTerm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .claude/skills/finding-discovery && 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 "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .claude/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discoveryType 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 vlinx-io/VelaTerm --skill finding-discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vlinx-io/VelaTerm finding-discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .agents/skills/finding-discovery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .agents/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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 vlinx-io/VelaTerm --skill finding-discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vlinx-io/VelaTerm finding-discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .cursor/skills/finding-discovery && 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 "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .cursor/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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/vlinx-io/VelaTerm.git --path src-tauri/resources/codex-security/skills/finding-discovery--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 vlinx-io/VelaTerm --skill finding-discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vlinx-io/VelaTerm finding-discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .gemini/skills/finding-discovery && 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 "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .gemini/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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 vlinx-io/VelaTerm finding-discoveryInstalls 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 vlinx-io/VelaTerm --skill finding-discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .github/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .github/skills/finding-discovery && 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 "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .github/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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 vlinx-io/VelaTerm --skill finding-discovery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vlinx-io/VelaTerm finding-discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src-tauri/resources/codex-security/skills/finding-discovery .opencode/skills/finding-discovery && 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 "finding-discovery" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/src-tauri/resources/codex-security/skills/finding-discovery into .opencode/skills/finding-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "finding-discovery", 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.
finding-discoveryA skill your agent uses when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change.
Finding Discovery is an agent skill from vlinx-io/VelaTerm. Use when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change. Do not use as the primary trigger for full PR, commit, branch, patch, or repository scans.
Its SKILL.md is about 6.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Security, covering Security review. The repository describes itself as: VelaTerm = Codex + iTerm2, The Best ADE for AI Coding. The licence is MIT.
Read from SKILL.md and the folder at commit 98b5f2f. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Finding Discovery loads about 6.3k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 3,260 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.
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.
The full file from vlinx-io/VelaTerm at commit 98b5f2f, republished under its MIT licence (© vlinx-io). 3,260 words, ~6,332 tokens.
.claude/skills/finding-discovery/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Investigate the proposed code or code changes for technically plausible security vulnerabilities using the threat model as context.
Standard and Deep discovery workers follow their self-contained coordinator prompts; they do not invoke this skill. For an explicit standalone repository-discovery request, apply the relevant checklist below directly to the authorized current source without running the diff-only workflow or starting another scan.
The path references in this skill are the default locations for this phase.
If the user explicitly provides a different path for a required input or output, use the user-provided path instead of the corresponding default path referenced in this skill.
If a required input is still missing, stop and ask the user for it before continuing.
Use the shared scan artifact path conventions in ../../references/scan-artifacts.md.
Read ../../references/security-guidance.md and resolve the applicable policy before inspecting each source file. A delegated file-review worker must do the same before reading its assigned source.
When a running diff scan already supplies its file inventory through list_codex_security_review_items, review that inventory directly and record all candidates once with record_codex_security_discovery_candidates. Do not generate ranked worklists, per-finding ledgers, discovery receipts, or discovery reports. Skip the legacy workflow and artifact requirements below.
For a targeted code diff without an existing compact inventory:
../security-scan/references/scan-artifacts-and-ledger.md.rank_input.jsonl deterministically from changed source-like files with <python_command> <plugin_dir>/scripts/generate_rank_input.py make-diff-rank-input --repo <repo_root> --base <base> --mode revisions --head <head> --out <discovery_dir>/rank_input.jsonl for PR, commit, and branch diffs, or <python_command> <plugin_dir>/scripts/generate_rank_input.py make-diff-rank-input --repo <repo_root> --base <base> --mode local-patch --out <discovery_dir>/rank_input.jsonl for a local patch.deep_review_input.jsonl with <python_command> <plugin_dir>/scripts/generate_rank_input.py copy-deep-review-input --rank-input <discovery_dir>/rank_input.jsonl --out <discovery_dir>/deep_review_input.jsonl. Diff scans do not rank or drop changed files before deep review.deep_review_input.jsonl using the shared scoped file-review rules.../security-scan/references/scan-artifacts-and-ledger.md#scoped-deep-review.Use this checklist to keep discovery specific without turning it into validation or attack-path analysis:
execute/executemany/executescript, pickle.load/pickle.loads/yaml.load/yaml.load_all, separate path/file helper methods, insert/select/delete/update query builders, or create/delete/reset/admin/job actions without auth, keep those operations as separate candidate instances when attackers can trigger them independently.to*Array, get*, getObject, numeric conversion, parse*, iterator, size, unchecked casts, and allocation loops. Treat these helpers as candidate root controls when malformed documents can trigger type confusion, exceptions, unbounded traversal, or memory/CPU exhaustion.perform, handle, or apply override. If the operation-specific helper splits, filters, canonicalizes, or rebuilds attacker-controlled paths before delegating to a shared evaluator or binder, use that helper line as the candidate root control.from, default-value, or type-resolution paths, keep the branch predicate and branch-local transform lines as affected locations when they bypass or narrow the shared validator. A shared helper finding does not close branch-specific root controls.downloadFrom, URL importers, webhook/callback clients, preview/render fetchers, and redirect-following HTTP clients, enumerate each attacker-controlled destination source and its closest allow/deny/filter/redirect control. Do not suppress SSRF because the fetch/callback is an intended feature, because filters are optional or empty by default, or because a sibling route found a louder file/path issue; keep the network row when user input can select a destination and the hard boundary is incomplete, operator-configured, or only pre-request.raw, url, or email does not close password, checkbox, confirmation, choice, or other nil/no-op typecheck branches that can still render into shell commands.FEATURE_SECURE_PROCESSING alone, swallowed/logged setFeature failures, or a safe default parser does not suppress caller-supplied parser factories/readers or converter paths that create SAX/DOM/StAX/Transformer sources from untrusted data.getDOM, cloneNode, signed-object lookup, subject confirmation, recipient, audience, destination, ACS URL, and issuer-binding lines when they decide which assertion is trusted or returned.foundValid* flag followed by a separate fixed-index, first/last-element, clone, serialization, or return path. Treat the later object-selection line as the broken control until exact counterevidence proves the validated object and consumed object are identical and equally bound.Realm classes before promoting a nearby generic HTTP auth finding. In TLS-upgraded or multi-step binds, keep the bind/rebind and principal/credential installation line candidate-visible.Version, VersionUtil, versionCompare, versionMatch, Capability, Feature, Negotiation, parseInt, split, matches, and comparator methods, then close paired validator/parser rows explicitly.relevant_lines only when the bug overlaps the diff and those lines are genuinely relevant to the issue.Prefer technically plausible candidates such as:
Discovery identifies plausible candidates and preserves their evidence; it does not own final severity calibration. For reportability and severity examples, defer to ../attack-path-analysis/references/severity-policy.md during attack-path analysis.
Avoid:
If there are no plausible candidates, return a no-findings result.
Otherwise, for each candidate include:
entrypoint/wrapper, root_control, sink, and concrete_implementation<family>:<file>:<line> for repository-wide and scoped-path scansrelevant_lines for diff-scoped scans when the bug overlaps the diff and those lines are relevant to the bugFor legacy diff-scoped discovery without a compact inventory, when candidates are emitted, create the per-finding directory from ../../references/scan-artifacts.md and append one discovery receipt to that finding's candidate ledger. The ledger row should identify the candidate, scan scope, discovery status, affected locations, and the discovery artifact or evidence that produced it.
../../references/scan-artifacts.md so later validation and attack-path analysis can prove coverage for that exact finding.relevant_lines when no bug exists. For diff-scoped scans, add relevant_lines only when the bug overlaps the diff and those lines are relevant to the bug.../../references/scan-artifacts.md.© vlinx-io, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in src-tauri/resources/codex-security/skills/finding-discovery of vlinx-io/VelaTerm.
Open the folder on GitHubat commit 98b5f2f
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in vlinx-io/VelaTerm, which our catalogue first saw on October 7, 2026.
Finding Discovery 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 |
|---|---|---|---|---|---|---|
| Finding Discovery this skillvlinx-io/VelaTerm | 270 | 1 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Deepsec Documentation Guidevercel-labs/deepsec | 8.1k | — | ~956 | Automated safety check: Pass | Apache-2.0 | |
| Kubernetes Network Security Auditkubeshark/kubeshark | 12k | — | ~7.3k | Automated safety check: Notes | Apache-2.0 | |
| Agentlas Security Scanagentlas-ai/Agentlas-OS | 1.6k | 1 repos | ~822 | Automated safety check: Pass | Apache-2.0 | |
| Native Dependency Updatemono/SkiaSharp | 5.6k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Semgrep Security Scantrailofbits/skills | 7.4k | — | ~3.7k | Automated safety check: Notes | CC-BY-SA-4.0 |
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.
kubeshark/kubeshark
Hunts for compromised workloads and malicious traffic in a Kubernetes cluster by sweeping network data through Kubeshark MCP, mapped to MITRE ATT&CK.
agentlas-ai/Agentlas-OS
A skill your agent uses when an agent folder must pass the Agentlas Cloud 2-stage security scan (static rules + BYOK LLM judgment) before private sync or public publish, or when asked to…
mono/SkiaSharp
Update native dependencies (libpng, libexpat, zlib, libwebp, harfbuzz, freetype, libjpeg-turbo, etc.) in SkiaSharp's Skia fork.
trailofbits/skills
Detects languages, proposes rulesets for approval, then runs the approved Semgrep scan across a codebase and merges the output into one SARIF file.
Fangcun-AI/SkillWard
Security-audit a third-party skill bundle (folder with SKILL.md, or .zip / .tar.gz archive) before installing it, using the SkillWard cloud scanner.
vlinx-io/VelaTerm
Assess an immutable patch artifact's program impact, regression risk, and auto-merge eligibility.
vlinx-io/VelaTerm
Explicitly spawn a standalone child session under the current vlx-term session, passing the task in as its first message (mirrors spawntask).
vlinx-io/VelaTerm
A skill your agent uses when the user asks for a deep, exhaustive, multi-pass, or variance-reducing repository-wide or scoped-path Codex Security scan.
vlinx-io/VelaTerm
Define, review, or update SECURITY.md guidance for a repository or component.
vlinx-io/VelaTerm
Track validated Codex Security findings in Linear, Jira, GitHub issues, or draft GitHub security advisories.
vlinx-io/VelaTerm
Use only when the user explicitly requests verification that a security fix remediates a reported vulnerability.
Categories
A skill your agent uses when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change. Finding Discovery is an agent skill from vlinx-io/VelaTerm. Use when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change.
Finding Discovery fits situations like: Codex is already in the finding-discovery phase of a security scan; the user explicitly asks to discover candidate security findings in a repository; repository scans.
Run `npx skills add vlinx-io/VelaTerm --skill finding-discovery -a claude-code`. Or copy the skill folder (src-tauri/resources/codex-security/skills/finding-discovery in vlinx-io/VelaTerm) into .claude/skills/finding-discovery in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vlinx-io/VelaTerm --skill finding-discovery -a codex`. Or copy the skill folder (src-tauri/resources/codex-security/skills/finding-discovery in vlinx-io/VelaTerm) into .agents/skills/finding-discovery in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vlinx-io/VelaTerm --skill finding-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/finding-discovery, .gemini/skills/finding-discovery, .github/skills/finding-discovery and .opencode/skills/finding-discovery in your project.
SKILL.md names no scripts, command-line tools or credentials: Finding Discovery is instructions for the agent only.
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.
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.
Finding Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 6.3k tokens (SKILL.md is roughly 25k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Finding Discovery: Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars), Agentlas Security Scan (agentlas-ai/Agentlas-OS, 1.6k stars) and Native Dependency Update (mono/SkiaSharp, 5.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vlinx-io (a GitHub user) maintains it in vlinx-io/VelaTerm, which has 270 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.
Source: vlinx-io/VelaTerm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.