Vercel Optimize Audit
vercel-labs/agent-skills
Runs a metrics-first audit of a deployed Vercel project, gating investigations on real signals to produce ranked, citation-backed cost and performance recommendations.
Agent skill
Runtime Evidence And Tracing
by hashgraph-online in hashgraph-online/awesome-codex-plugins
A skill your agent uses when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
Install Runtime Evidence And Tracing
$ npx skills add hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracing --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .claude/skills/runtime-evidence-and-tracing && 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 "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .claude/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracingType 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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .agents/skills/runtime-evidence-and-tracing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .agents/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .cursor/skills/runtime-evidence-and-tracing && 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 "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .cursor/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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/hashgraph-online/awesome-codex-plugins.git --path plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing--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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .gemini/skills/runtime-evidence-and-tracing && 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 "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .gemini/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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 hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracingInstalls 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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .github/skills/runtime-evidence-and-tracing && 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 "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .github/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins runtime-evidence-and-tracing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing .opencode/skills/runtime-evidence-and-tracing && 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 "runtime-evidence-and-tracing" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing into .opencode/skills/runtime-evidence-and-tracing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "runtime-evidence-and-tracing", 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
runtime-evidence-and-tracing- GitHub stars
- 1.3k
- Token cost
- ~950 tokens
- SKILL.md length
- 410 words
- Files
- 3 (incl. references)
- Skills in repo
- 714
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A skill your agent uses when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
- Works in 7 steps: Search request wrappers, service… → Confirm whether the calling surface can… → If no evidence contract exists,… → …
- Connecting observed behavior
- SKILL.md covers Overview, When To Use, Inputs Needed and Execution Order, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Runtime Evidence And Tracing is an agent skill from hashgraph-online/awesome-codex-plugins. Use when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
Its SKILL.md is about 950 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/build-when-missing.md` and `references/runtime-profile-policy.md`).
It sits in DevOps & Cloud, covering Observability. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
When your agent uses it
- Connecting observed behavior
- External dependency results
- Artifacts into a runtime evidence loop
Example prompts
- “/runtime-evidence-and-tracing”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Search request wrappers, service entrypoints, logs, metrics, and trace scripts.
- Confirm whether the calling surface can generate or propagate X-Request-ID and X-Harness-Run-ID.
- If no evidence contract exists, bootstrap the minimum run artifact contract from references/build-when-missing.md.
- Design artifacts/runs// with manifest, summary, logs, network, screenshots, and trace files.
- Define the collection order for the target flow: start, authenticate if needed, operate, wait, read artifacts, and attribute the result.
- Define blocker categories: code regression, environment unavailable, external dependency unavailable, data missing, and not evaluable.
- Explain how PRs or ledgers should reference artifacts without committing large temporary files.
What it can do on your machine
Read from SKILL.md and the folder at commit 9e7b281. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
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
Runtime Evidence And Tracing loads about 950 tokens when it runs, and up to ~1.8k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 410 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 hashgraph-online/awesome-codex-plugins at commit 9e7b281, republished under its Apache-2.0 licence (© hashgraph-online). 410 words, ~950 tokens.
Download SKILL.mdSave it as
.claude/skills/runtime-evidence-and-tracing/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- runtime-evidence-and-tracing
- description
- Use when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
Runtime Evidence And Tracing
Overview
Make runtime validation auditable by tying observed behavior to runtime evidence through stable IDs and artifacts.
Agents should not only say they tested something; they should leave run IDs, request IDs, logs, screenshots, interaction records, or traces. For shared harness terms, see ../../references/harness-patterns.md; when evidence surfaces are absent, use references/build-when-missing.md. For neutral runtime profiles and redaction policy, see references/runtime-profile-policy.md.
When To Use
- The user asks to connect, diagnose, or design interactive validation, runtime validation, request IDs, traces, logs, metrics, or artifacts.
- A production or test-environment issue must be traced from observed behavior to runtime evidence.
- A flow with external dependencies needs classification as code failure, dependency blocker, environment issue, or data problem.
Inputs Needed
- Target flow, entry action, command, or interface.
- Existing logging, request wrapper, headers, and observability endpoints.
- Artifact directory and run ID naming preference.
Execution Order
- First: Find the request entrypoint and existing request/log/trace propagation points.
- Then: Design run IDs, request IDs, artifact bundles, and collection commands.
- Finally: Output the evidence contract and validation path, including fallback and blocker classification.
Step-by-Step Process
- Search request wrappers, service entrypoints, logs, metrics, and trace scripts.
- Confirm whether the calling surface can generate or propagate
X-Request-IDandX-Harness-Run-ID. - If no evidence contract exists, bootstrap the minimum run artifact contract from
references/build-when-missing.md. - Design
artifacts/runs/<run_id>/with manifest, summary, logs, network, screenshots, and trace files. - Define the collection order for the target flow: start, authenticate if needed, operate, wait, read artifacts, and attribute the result.
- Define blocker categories: code regression, environment unavailable, external dependency unavailable, data missing, and not evaluable.
- Explain how PRs or ledgers should reference artifacts without committing large temporary files.
Show full SKILL.md (130 more words)Show less
Checks
- Propagation: request ID and run ID remain searchable across caller, service, job, and external dependency evidence.
- Artifact: the directory includes manifest, summary, and reproducible commands.
- Evidence: screenshots, console, network, logs, and metrics cover the failure boundary.
- Attribution: external dependency or environment blockers are not reported as product-quality failures.
- Privacy: artifacts do not contain tokens, phone numbers, real secrets, or sensitive payloads.
Output Format
# Runtime Evidence And Tracing
## Detected Mapping
- runtime-evidence:
- validation:
- ledger:
## ID Contract
- Run ID:
- Request ID:
- Header propagation:
## Artifact Bundle
-
## Collection Flow
1.
2.
3.
## Failure Classification
-
## PR / Ledger Reference
-Common Mistakes
- Keeping only screenshots with no request ID or runtime evidence.
- Creating traces only in one layer, leaving observed failures disconnected.
- Treating external account or quota issues as product-quality failures.
- Committing large artifacts instead of referencing paths and summaries.
Example Prompts
- "Connect interactive validation to request IDs."
- "Design artifacts/runs evidence for this runtime workflow."
- "How should this failure be classified: code, environment, or external blocker?"
© hashgraph-online, 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
SKILL.md and 2 other files (references) in plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing of hashgraph-online/awesome-codex-plugins.
- SKILL.md
- references/build-when-missing.md
- references/runtime-profile-policy.md
Open the folder on GitHubat commit 9e7b281
Compare with similar skills
Runtime Evidence And Tracing 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 |
|---|---|---|---|---|---|---|
| Runtime Evidence And Tracing this skillhashgraph-online/awesome-codex-plugins | 1.3k | — | ~950 | Automated safety check: Pass | Apache-2.0 | |
| Vercel Optimize Auditvercel-labs/agent-skills | 32k | 8 repos | ~4.3k | Automated safety check: Pass | None | |
| Kubeshark Installerkubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| Kubeshark KFL2 Filter Referencekubeshark/kubeshark | 12k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | |
| KubeSphere ServiceMesh Managerkubesphere/kubesphere | 17k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Kubernetes Network Root Cause Analysiskubeshark/kubeshark | 12k | — | ~5.3k | Automated safety check: Pass | Apache-2.0 |
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Categories
Questions about Runtime Evidence And Tracing
What does Runtime Evidence And Tracing do?
A skill your agent uses when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop. Runtime Evidence And Tracing is an agent skill from hashgraph-online/awesome-codex-plugins. Use when connecting observed behavior, logs, metrics, request IDs, run IDs, screenshots, traces, external dependency results, or artifacts into a runtime evidence loop.
When should I use Runtime Evidence And Tracing?
Runtime Evidence And Tracing fits situations like: connecting observed behavior; external dependency results; artifacts into a runtime evidence loop.
How do I install Runtime Evidence And Tracing in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a claude-code`. Or copy the skill folder (plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing in hashgraph-online/awesome-codex-plugins) into .claude/skills/runtime-evidence-and-tracing in your project. Claude Code loads it when a task matches its description.
How do I install Runtime Evidence And Tracing in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a codex`. Or copy the skill folder (plugins/yfge/agent-harness-skills/skills/runtime-evidence-and-tracing in hashgraph-online/awesome-codex-plugins) into .agents/skills/runtime-evidence-and-tracing in your project. Codex loads it when a task matches its description.
Can I use Runtime Evidence And Tracing 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 hashgraph-online/awesome-codex-plugins --skill runtime-evidence-and-tracing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/runtime-evidence-and-tracing, .gemini/skills/runtime-evidence-and-tracing, .github/skills/runtime-evidence-and-tracing and .opencode/skills/runtime-evidence-and-tracing in your project.
What does Runtime Evidence And Tracing need to run?
SKILL.md names no scripts, command-line tools or credentials: Runtime Evidence And Tracing is instructions for the agent only.
Does Runtime Evidence And Tracing 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 Runtime Evidence And Tracing 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 Runtime Evidence And Tracing use?
Runtime Evidence And Tracing 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 Runtime Evidence And Tracing use?
About 950 tokens (SKILL.md is roughly 3.8k 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 800 tokens, read only when the agent opens those files.
What are the alternatives to Runtime Evidence And Tracing?
Skills that share tags, products or a category with Runtime Evidence And Tracing: Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars), Kubeshark Installer (kubeshark/kubeshark, 12k stars), Kubeshark KFL2 Filter Reference (kubeshark/kubeshark, 12k stars) and KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Runtime Evidence And Tracing?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,255 GitHub stars. The repository holds 714 skills in this directory. The repository was last updated on October 9, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.