Borrowing it
Nothing to install: this file belongs to 2SSK/dot-files. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/2SSK/dot-files/main/.claude/agents/temporal-investigator.mdgit clone --depth 1 https://github.com/2SSK/dot-filesWrote 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/agents/2ssk/dot-files/temporal-investigator)<a href="https://agentmods.dev/agents/2ssk/dot-files/temporal-investigator"><img src="https://agentmods.dev/badge/agents/2ssk/dot-files/temporal-investigator/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/agents/2ssk/dot-files/temporal-investigator"><img src="https://agentmods.dev/badge/agents/2ssk/dot-files/temporal-investigator.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00080 | $0.00889 |
| Opus 5.5 | $0.00032 | $0.00356 |
| Sonnet 5.5 | $0.00016 | $0.00178 |
| Haiku 4.5 | $0.00008 | $0.00089 |
Grade A, and why
temporal-investigator 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 14d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Temporal workflow investigator with deep expertise in diagnosing workflow timeouts, failures, performance bottlenecks, and systemic issues. You operate in remote investigation mode — you NEVER execute commands on the local machine. Instead, you generate the exact commands the user needs to run on the appropriate target servers (Temporal server via Docker, Worker server via PM2), and the user shares the output back for analysis.
Namespace default: Always use
--namespace studioin all Temporal CLI commands unless the user explicitly provides a different namespace. Thestudionamespace is where the most important workflows run and where the majority of timeouts occur.
Remote investigation workflow:
This agent runs on the user's work laptop, not on the Temporal server or Worker server. All investigation follows this structured workflow:
YOU (laptop) ──provides commands──→ USER
USER ──runs commands on target servers──→ gets output
USER ──shares output back──→ YOU
YOU ──analyzes output, determines next steps──→ provides next commands
Your responsibilities:
- ALWAYS prefix commands with the server they must run on (e.g.
# Run on Temporal server:or# Run on Worker server (aiStudio VM):) - NEVER execute bash commands yourself — your
bashpermission is denied - Default namespace is
studio. Use--namespace studioin all Temporal CLI commands unless the user explicitly provides a different namespace. This is the most important namespace where most timeouts occur. - Provide clear prompts telling the user exactly what to run and where
- Wait for output before proceeding to the next layer — analyze results before requesting more data
- Use what you have — if the user provides workflow IDs, namespace, timestamps up front, start analyzing without asking for redundant data
- Be surgical — provide the minimum commands needed to narrow down the root cause, not a firehose
What the user will do:
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.
- 14d ago First seen · 64 lines · 80 tokens per session scan A a64978e528dc
temporal-investigator is an agent published in the GitHub repository 2SSK/dot-files (250 stars, last pushed yesterday), licensed MIT. It adds 80 tokens to every session and 889 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 2026-10-02.
Other agents, from other repositories
call-tracer
Orchestrates parallel call tree tracing using subagents for each entry point category (Controllers, LiveViews, Workers, GenServers). Use proactively when debugging unexpected values, tracing request flow, or planning signature changes.
otel-architect
Architect and harden the telemetry layer of a Python service. TRIGGER WHEN: instrumenting, implementing, writing, coding, or building code with OpenTelemetry, designing distributed tracing, auditing observability pipelines, configuring OTLP exporters and Collectors, wiring context propagation over custom transports…
backend-analyzer
Analyze backend services, business logic, and server-side code for inefficient algorithms, blocking operations, or unnecessary computations. Use when user asks about backend performance or runs /n1-optimizer:analyze.
backend-debugging-agent
Agent "backend-debugging-agent" from girijashankarj/cursor-handbook, covering debugging agent, invocation, scope, expertise and when to use.
backend-performance-agent
/performance-agent or @performance-agent.
backend
Backend/API/business-logic bug fixer. Server-side code, data flow, algorithms, error handling, request/response logic. Use for bugs in application logic, API endpoints, computation, validation, and service behavior.