add-your-agent
Use when putting the agent in this repository on a Veris Bench bench as a "Your image" candidate, when updating that candidate to a new version, or when its bench attempts show empty replies, failed tool calls, no model calls for the grader, or never reach the bench's twins.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/veris-ai/plugins --skill add-your-agent- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads add-your-agent automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Add your agent to Veris Bench
Take the agent in this repository to a registered Your image candidate on a Veris Bench bench, and prove it works with a smoke trial.
The agent is the constant. Add one server file, a Dockerfile and a candidate file beside the agent. Change the agent's own code only when there is no other way, and say so in your report.
A smoke attempt that is completed does not prove the integration works. An
agent whose database calls all fail, or whose model calls the grader cannot
see, still completes. Step 9 says what to check.
Read reference/api.md before step 1 and reference/image.md before step 2.
Inputs
Collect these before you change anything. Ask the user for what is missing.
| Input | Where it comes from |
|---|---|
VERIS_API_KEY | Environment variable, starts with vbk_. Only a person can issue one: console, Overview, API keys, Issue. Never print it or write it to a file. |
BENCH_API | Default https://bench.api.veris.ai/v1. Use another only when the user gives one. |
BENCH_ID | The skill's argument, if the user gave one. Otherwise ask, or list their benches and have them choose. |
| Registry | A repository prefix Docker can push to, such as ghcr.io/<org>. |
| Model keys | The secrets the agent reads, such as OPENAI_API_KEY. They go in the bench, never in the image or the repository. The user adds a missing one in the console, unless it is already in your environment. |
Steps
- Check access. Read the bench.
accessmust bewrite. If it isread, stop and tell the user why (reference/api.md, "Access"). - Read the agent, without editing. Write down: language and entry point;
the function that runs one conversation turn and how it keeps history; the
model SDK and its installed version; every external service it calls and
where each address or DSN comes from (variable, config file or a literal);
every secret it reads; and files it opens by a relative path. Check the SDK
against "Telemetry" in
reference/image.mdnow: an unsupported version records no model calls and says nothing. - Read the bench's world. List its services (
reference/api.md, "World"). Match each service the agent calls to a twin. Tell the user about any service the agent calls that has no twin: those calls reach the real vendor, unless Veris turned on the gateway for the bench. - Add the server file,
bench_server.pyorbench_server.mjs, from the pattern inreference/image.md. It wraps the agent's turn function, keeps one conversation per session id, serves/health, and listens on0.0.0.0:8008. Use http. Use ws only if the agent already speaks WebSocket. - Point the agent at the twins, in the server file. Before the agent's
modules load, copy each twin's address from
VERIS_DS_SERVICE_URLSinto the setting the agent already reads. Apply the client fixes inreference/image.md, "Twins". - Write the Dockerfile and
.dockerignorefromreference/image.md. If the repository has a Dockerfile, reuse it when it can run the server. - Check locally. Build for
linux/amd64, run it, and send/healthand one turn (reference/image.md, "Local check"). Fix anything that fails here before you push. - Push and register. Push, pin by digest, run
check-image, save a registry login if needed, make sure each secret is in the bench's candidate-env, writebench/candidate.json, and register the candidate (reference/api.md). - Run a smoke trial and verify it. Two tasks that need the agent's tools, no personas, one repeat. When nothing is pending, check every attempt against the table below. Each row that fails is an integration bug: find the cause in its artifacts, fix it, push a new digest, update the candidate, re-run it in the same trial once nothing is pending, and check again.
- Report (format below).
Done means every smoke attempt shows this
| Check | Where to read it (reference/api.md, "Verify") | If it fails |
|---|---|---|
| It ran | status is completed | Read the end of error: it holds your container's last log lines. |
| The agent answered | turns is 2 or more, and the transcript has agent replies | Wrong path or field mapping, or the server crashed on a turn. Read candidate.log and transcript.jsonl. |
| The grader sees the model calls | agent_trace_reason is null, and agent_trace.json has llm_calls above 0 | See "Telemetry" in reference/image.md. agent_trace_reason alone is not enough: it is null when the trace holds no model call. judge_disabled_trace means the bench's grader doesn't read traces: not a bug, skip this check. |
| The agent used its tools | tool_calls above 0 if the agent has tools, and the tool results in agent_trace.json are not errors | A tool error that names a connection or a certificate is step 5; read "Twins" in reference/image.md. |
| It reached the twins | each twin the agent uses received at least one request from it (reached in the Verify command) | The agent is still pointed at its own default address. Redo step 5. Don't use ledger_summary counts for this: they include requests the platform makes. |
passed is not on this list. Whether the agent passes a task measures the
agent, not the integration. Two attempts say little about quality; a full trial
does.
Traps that look like success
| Symptom | Cause | Fix |
|---|---|---|
Node agent: every database tool fails, and the log has a pg SSL warning | node-postgres treats the twin DSN's sslmode=require as verify-full, and the twin's certificate is self-signed | Append uselibpqcompat=true to the DSN in the server file |
Node agent: agent_trace_reason is no_spans_received | The trace hook writes into the working directory, which the run user can't write | The run user owns the app directory (chown) |
Node agent: llm_calls is 0, and candidate.log has no veris-otel-node: instrumented OpenAI line | The openai package is older than 5 | Upgrade openai to 5 or later, and update the lockfile so the image build installs it |
The attempt fails within a minute, exec format error or a pull error | An arm64 image built on Apple Silicon, or the bench can't pull it | --platform linux/amd64; run check-image |
| Agent replies are empty | image.path or the response field doesn't match the server | Match bench/candidate.json to the server |
| Tools fail only on the bench | A literal address, or a variable the bench doesn't set | Step 5 |
Report to the user
- The files you added or changed, one line each.
- The image reference, candidate id and trial id, and the console link
https://benchmark.veris.ai/benchmarks/<bench id>?trial=<trial id>. - For each smoke attempt: the five checks, and
passed. - Any change to the agent's own code or dependencies, and why.
- Every fix you made after the first smoke run, and why.
- Next: a full trial, as on https://docs.veris.ai/run-a-trial, and for a new version, a new candidate in the same trial.
FAQ
What does the add-your-agent skill do?
Use when putting the agent in this repository on a Veris Bench bench as a "Your image" candidate, when updating that candidate to a new version, or when its bench attempts show empty replies, failed tool calls, no model calls for the grader, or never reach the bench's twins.
How do I install add-your-agent?
Run npx skills add https://github.com/veris-ai/plugins --skill add-your-agent in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/add-your-agent/ (personal) or .claude/skills/add-your-agent/ (project).
Which AI agents can use add-your-agent?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is add-your-agent safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains add-your-agent?
It is published by veris-ai in veris-ai/plugins. It has 48 recorded installs.
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