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 ArabelaTso/Skills-4-SE --skill replay-oriented-instrumentationgit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote 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/arabelatso/skills-4-se/replay-oriented-instrumentation)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/replay-oriented-instrumentation"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/replay-oriented-instrumentation/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/arabelatso/skills-4-se/replay-oriented-instrumentation"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/replay-oriented-instrumentation.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 | $0.00097 | $0.02174 |
| Opus 5 | $0.00048 | $0.01087 |
| Sonnet 5 | $0.00019 | $0.00435 |
| Haiku 4.5 | $0.00010 | $0.00217 |
Grade A, and why
replay-oriented-instrumentation 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 9d 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 — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Replay-Oriented Instrumentation
Instrument programs to capture execution information that enables deterministic replay, making it possible to reproduce and debug failures that are difficult to reproduce normally.
Core Concept
Deterministic replay works by:
- Recording: Capture all non-deterministic inputs during execution
- Replaying: Re-execute the program using recorded inputs to reproduce exact behavior
- Debugging: Use replay to analyze failures with time-travel debugging
Workflow
1. Identify Non-Determinism Sources
Analyze the program to find sources of non-determinism. See references/non-determinism.md for comprehensive coverage.
Common sources:
- I/O operations: File reads, network requests, user input
- Time: System clock, timestamps, timeouts
- Randomness: Random number generation, hash functions
- Threading: Thread scheduling, race conditions, lock ordering
- System state: Process IDs, memory addresses, environment variables
2. Choose Recording Granularity
Select appropriate recording level based on needs:
Function-level (recommended starting point):
- Record function calls and return values
- Low overhead
- Good for most debugging scenarios
- Example: Record all I/O function calls
Event-based (balanced approach):
- Record specific non-deterministic events
- Moderate overhead
- Captures essential non-determinism
- Example: Record syscalls, thread events, random values
Instruction-level (comprehensive):
- Record every instruction execution
- High overhead, large logs
- Complete determinism
- Use only when necessary
3. Implement Recording Infrastructure
Choose between custom instrumentation or existing tools:
Custom instrumentation (flexible):
- Wrap non-deterministic functions
- Log inputs and outputs
- Control what gets recorded
- See language-specific guides below
Existing tools (easier):
- Use established replay frameworks
- Less implementation effort
- May have limitations
- See references/replay-tools.md
What ships with it
3 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.
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.
- 9d ago First seen · 365 lines · 97 tokens per session scan A c74442e63e89
replay-oriented-instrumentation is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (252 stars, last pushed 22d ago), licensed Apache-2.0. It adds 97 tokens to every session and 2,174 once invoked, about $0.0005 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 2026-09-03.
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