Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add monte-carlo-data/mc-agent-toolkit --skill instrument-agentgit clone --depth 1 https://github.com/monte-carlo-data/mc-agent-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/instrument-agent)<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/instrument-agent"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/instrument-agent.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.02719 |
| Opus 5 | $0.00028 | $0.01359 |
| Sonnet 5 | $0.00011 | $0.00544 |
| Haiku 4.5 | $0.00006 | $0.00272 |
Grade A, and why
monte-carlo-instrument-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monte Carlo Instrument-Agent Skill
This skill walks an MC Agent Observability customer through instrumenting a new AI agent in their Python codebase: detect AI libraries → install the Monte Carlo OpenTelemetry SDK + matching instrumentors → generate mc.setup() (with SimpleSpanProcessor when serverless) → propose @trace_with_workflow / @trace_with_task decorator diffs → confirm env vars (only when needed) → verify traces flow via get_agent_metadata.
The skill produces traces. It is not for monitoring or alerting on existing traces — that's monte-carlo-monitoring-advisor. The two skills are sequential: instrument-agent first, monitoring-advisor afterward.
Monte Carlo tool routing (required): Always call Monte Carlo MCP tools through this plugin's bundled server, whose fully-qualified tool names are
mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__<tool>(e.g.mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__get_alerts). Bare tool names used in this skill (get_alerts,search,get_table, …) refer to that bundled server. If the session also has a separately-configuredmonte-carlo-mcpserver, do not route to it — it may point at a different endpoint or credentials.
Reference files live next to this file. Use the Read tool (not MCP resources) to access them.
CRITICAL — Never modify any file without explicit user approval
This skill must not modify any file in the customer's codebase without explicit per-file user approval. This rule covers:
- Dependency files —
requirements.txt,pyproject.toml,Pipfile, lockfiles. Always propose the diff and wait for confirmation before editing. - Source code —
mc.setup()insertion, decorator placement (@trace_with_workflow,@trace_with_task), import additions. Always propose the diff and wait for confirmation per file. - Env files —
.env,.envrc, shell rc files. Always propose the change and wait for confirmation before editing.
The skill walks the user through what needs to change and why, then proposes diffs. It does not apply edits, run pip install, or write env files autonomously. The only exception: the user may explicitly waive approval for a specific file ("I know the risks, just edit the file") — proceed for that file only and surface that the approval was waived.
What ships with it
32 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/decorator-placement.md 7.9 KB
- references/library-detection.md 14 KB
- references/redaction.md 14 KB
- references/setup-template.md 22 KB
- references/troubleshooting.md 11 KB
- references/verify-traces.md 8.1 KB
- references/workflow.md 19 KB
- scripts/detect_libraries.py 19 KB runs code
- scripts/fetch_sdk_docs.py 12 KB runs code
- tests/fixtures/boto3-only/requirements.txt 31 B
- tests/fixtures/existing-setup/requirements.txt 17 B
- tests/fixtures/existing-setup/src/tracing_alias.py 146 B runs code
- tests/fixtures/existing-setup/src/tracing_direct.py 162 B runs code
- tests/fixtures/existing-setup/src/tracing.py 140 B runs code
- tests/fixtures/mixed-requirements-pyproject/pyproject.toml 299 B
- tests/fixtures/mixed-requirements-pyproject/requirements.txt 12 B
- tests/fixtures/no-deps/README.md 225 B
- tests/fixtures/pep621-pyproject/pyproject.toml 317 B
- tests/fixtures/pipfile/Pipfile 194 B
- tests/fixtures/poetry-pyproject/pyproject.toml 345 B
- tests/fixtures/requirements/requirements.txt 194 B
- tests/fixtures/sample_agent/agent.py 1.4 KB runs code
- tests/fixtures/sample_agent/requirements.txt 74 B
- tests/fixtures/sample_agent/traced_entrypoint.py 109 B runs code
- tests/fixtures/sample_serverless_agent/agent.py 1.5 KB runs code
- tests/fixtures/sample_serverless_agent/requirements.txt 104 B
- tests/fixtures/sample_serverless_agent/serverless.yml 358 B
- tests/fixtures/serverless/app.py 50 B runs code
- tests/fixtures/serverless/requirements.txt 17 B
- tests/fixtures/serverless/serverless.yml 32 B
- tests/test_detect_libraries.py 11 KB runs code
- tests/test_fetch_sdk_docs.py 14 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 125 lines · 56 tokens per session scan A 6ed1c7b5194f
monte-carlo-instrument-agent is a skill published in the GitHub repository monte-carlo-data/mc-agent-toolkit (91 stars, last pushed 13d ago), licensed Apache-2.0. It adds 56 tokens to every session and 2,719 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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