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 icesixgod/codex-trajectory --skill inspect-codex-trajectorygit clone --depth 1 https://github.com/icesixgod/codex-trajectoryWrote 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/icesixgod/codex-trajectory/inspect-codex-trajectory)<a href="https://agentmods.dev/skills/icesixgod/codex-trajectory/inspect-codex-trajectory"><img src="https://agentmods.dev/badge/skills/icesixgod/codex-trajectory/inspect-codex-trajectory/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/icesixgod/codex-trajectory/inspect-codex-trajectory"><img src="https://agentmods.dev/badge/skills/icesixgod/codex-trajectory/inspect-codex-trajectory.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 | $0.00088 | $0.00982 |
| Opus 5.5 | $0.00035 | $0.00393 |
| Sonnet 5.5 | $0.00018 | $0.00196 |
| Haiku 4.5 | $0.00009 | $0.00098 |
Grade A, and why
inspect-codex-trajectory 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 today.
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 — 21 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inspect Codex Trajectory
Use the plugin's session MCP tools instead of opening raw files under the Codex home directory.
- For the current task, use a caller-provided verified session ID, or call
list_codex_sessionsand select the matching exact ID before callingshow_codex_trajectory. Omit the ID only when the user requests the latest modified active task; omission is not caller binding and excludes archives by default. Keep the defaultdetailLevel: summary; this renders the interactive trajectory UI without tool inputs or outputs. - For a historical task, call
list_codex_sessions(setincludeArchived: trueonly when archived history is wanted), choose the exact session ID, then callshow_codex_trajectorywith that ID. - Use
get_codex_trajectorywhen the user wants analysis without the interactive UI. Cite turn numbers and record indexes from its structured result. If the requested evidence predates the returned page, call it again with the response'spagination.nextBeforeRecordasbeforeRecord; continue only as far back as the request requires. - When the user wants a live or picture-in-picture view, call
show_codex_trajectoryin summary mode. The user can click Live window. Codex uses its supported side panel with task Token totals, quota windows, and a chronological safe-summary event stream; regular Chromium hosts can use native video PiP. The native right-panel Codex Trajectory entry can also open the calling task without a model turn. Status and quotas reflect persisted samples. The viewer provides no stopping or automatic-stop feature. Do not call the app-only native-entry or live-update helpers as model tools. - Supply the exact selected session ID and use
detailLevel: fullonly after the user explicitly asks to inspect full tool input or output. Treat those values as potentially sensitive and quote no more than the task requires. Never exposesession_meta.base_instructions, encrypted reasoning, credentials, or environment variables. - Explain that Codex logs do not expose DeepSeek Harness step boundaries directly. The plugin starts a new approximate step when model output resumes after one or more tool results.
- Treat read warnings as evidence of skipped malformed records. If a paginated lineage fails validation, report that the local task history is inconsistent; do not bypass the plugin by opening inherited rollout files directly.
- A
read-limit-exceededresult means the selected log exceeds its byte budget, not that the task is missing. The viewer's error page shows the size and lets the user choose a larger limit. Keep the default 512 MiB unless the user explicitly chooses or requests a larger budget; pass the chosen byte count asmaxReadByteswith an explicitsessionIdon subsequent reads. Never enable full details merely because a larger read budget was approved. Other line, page, cache, lineage, and filesystem checks continue to apply. - For current-task timing or local versus model/token time, call
get_codex_project_timingwith the verified selected task ID. The tool keeps its original name for compatibility and now reads only that task, reusing its loaded source/index when available. Report durations and percentages fromtiming, and disclose untimed turns/tools when nonzero. DistinguishmissingTimingToolsandinvalidTimingToolsfromzeroDurationToolsandsubmillisecondTools: zero/below-precision calls do not block estimates, while missing/invalid calls reserve their possible execution windows as unattributed. A null duration in a public trajectory record alone does not reveal its timing quality. Explain that active time excludes gaps between turns and parallel tools count once. Model/token time includes estimated response/network/queueing waits and cannot isolate pure token generation. Do not infer time from token counts or reinterpret unattributed time as model time. For the visual view, open the task trajectory and use Calculate task timing.
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.
- today Changed · +1 lines · +10 tokens per session 2f46be20ab46
- 19d ago Changed · +1 lines 85e62d9aa569
- 1mo ago First seen · 19 lines · 78 tokens per session scan A 29da5b70032d
inspect-codex-trajectory is a skill published in the GitHub repository icesixgod/codex-trajectory (250 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 982 once invoked, about $0.0004 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.
Other skills, from other repositories
matlab-integrate-pytorch-vision
Creates MATLAB interfaces to Python image processing and computer vision models from GitHub repositories or pip-installable packages using MPyReq. Use when asked to interface MATLAB with a Python CV/image model (segmentation, depth estimation, object detection, image generation, super-resolution, etc.), given a GitHub…
sdlc-domain-boundary-modeling
Use to model bounded contexts, capabilities, ownership, domain data/language, allowed interactions, and forbidden dependencies.
dev-prompt-evaluation
Use to design, test, compare, version, and validate prompts or LLM behavior with measurable criteria and datasets.
optimize-for-gpu
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS…
developing-genkit-python
Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
thinking-out-loud
A contract for what the agent does when a long, messy, stream-of-consciousness ramble arrives (usually voice dictation): act on nothing until the echo brief is approved. The echo audits the entire transfer, mission, locked decisions and constraints, open questions, flips and parked tangents, with the model's…