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 UKGovernmentBEIS/inspect_evals --skill check-trajectories-workflowgit clone --depth 1 https://github.com/UKGovernmentBEIS/inspect_evalsWrote 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/ukgovernmentbeis/inspect_evals/check-trajectories-workflow)<a href="https://agentmods.dev/skills/ukgovernmentbeis/inspect_evals/check-trajectories-workflow"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/check-trajectories-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ukgovernmentbeis/inspect_evals/check-trajectories-workflow"><img src="https://agentmods.dev/badge/skills/ukgovernmentbeis/inspect_evals/check-trajectories-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00069 | $0.01098 |
| Opus 5.5 | $0.00028 | $0.00439 |
| Sonnet 5.5 | $0.00014 | $0.00220 |
| Haiku 4.5 | $0.00007 | $0.00110 |
Grade A, and why
check-trajectories-workflow 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 2mo 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Check Agent Trajectories
This workflow uses Inspect Scout to automatically analyze agent trajectories. It's faster than manual analysis but may miss nuanced issues.
Workflow Steps
-
If the user does not give any indication of what log file to use, ask them for which log file or files they want the workflow performed on. You can show them the most recent log file in logs/ and ask them if that's what they want.
-
Determine the name of the evaluation the log file is used in, and create a folder titled
agent_artefacts/trajectory_analysis/<eval_name>. Add a number to the end if the folder already exists. -
Read agent_artefacts/trajectory_analysis/inspect_scout/scanners.py to see what the default scanners check for:
- outcome_summary: Brief summary of why the agent succeeded or failed.
- external_failure: Failed due to CAPTCHAs, rate limiting, network issues, missing dependencies.
- formatting_failure: Failed due to incorrect answer formatting despite correct answer.
- reward_hacking_success: Succeeded through reward hacking or unintended means.
- ethical_refusal: Failed because the agent refused on ethical or safety grounds.
Additionally, if
agent_artefacts/trajectory_analysis/<eval_name><version>exists already, check for any scanners contained in the latest version and include those. -
Tell the user what will be checked by default and ask if they want to check for anything else.
-
If the user wants additional checks, create an eval_scanners.py file under
agent_artefacts/trajectory_analysis/<eval_name>/, and add Inspect Scout scanners that check for their requirements. Use the existing scanners inagent_artefacts/trajectory_analysis/inspect_scout/scanners.pyand the Inspect Scout documentation as references. Copy any scanners found in the eval_name folder at the end of Step 2 across as well.Each custom scanner should be wrapped in an
InspectEvalScannerobject and added to aSCANNERSlist:
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.
- 2mo ago First seen · 63 lines · 69 tokens per session scan A 9af8d4ac27f7
check-trajectories-workflow is a skill published in the GitHub repository UKGovernmentBEIS/inspect_evals (721 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 1,098 once invoked, about $0.0003 per session on Opus 5.5. 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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