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 agentmods add skills/youglin-dev/aha-loop/observabilitynpx skills add YougLin-dev/Aha-Loop --skill observabilitygit clone --depth 1 https://github.com/YougLin-dev/Aha-LoopWhat 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 | $0.00022 | $0.01581 |
| Opus 5 | $0.00011 | $0.00790 |
| Sonnet 5 | $0.00004 | $0.00316 |
| Haiku 4.5 | $0.00002 | $0.00158 |
Grade A, and why
observability 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 2d 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability Skill
Maintain transparent, human-readable logs of AI decision-making process.
Workspace Mode Note
When running in workspace mode, log to .aha-loop/logs/ai-thoughts.md instead of logs/ai-thoughts.md.
The orchestrator will provide the actual paths in the prompt context.
The Job
- Log significant thoughts and decisions to
logs/ai-thoughts.md - Provide visibility into AI reasoning process
- Create anchors for humans to understand what's happening
- Never hide failures or uncertainty
When to Log
Always Log
- Starting a new task - What am I about to do and why
- Major decisions - When choosing between approaches
- Unexpected findings - Something surprising or important
- Errors and recovery - What went wrong and how I'm handling it
- Completion - What was accomplished
Optional Log (Detailed Level)
- Intermediate steps
- Research findings
- Minor decisions
- Progress updates
Log Format
Append to logs/ai-thoughts.md:
## 2026-01-29 14:30:00 | Task: PRD-003 | Phase: Research
### Context
I'm researching authentication strategies for the web app. This is critical
because it affects security architecture and user experience.
### Inner Thoughts
The vision mentions "simple" and "quick to use". Traditional username/password
might add friction. Considering passwordless options but need to evaluate
complexity tradeoffs.
### Decision Point
- Considering: Traditional email/password
- Considering: Magic link (passwordless)
- Considering: OAuth only (Google/GitHub)
- **Chosen:** Magic link with OAuth fallback
- **Reason:** Aligns with "simple" goal, reduces password fatigue,
OAuth provides familiar alternative
### Current Progress
- [x] Read vision requirements
- [x] Research auth options
- [ ] Prototype magic link flow
- [ ] Evaluate email service options
### Observations
- Magic link requires reliable email delivery
- Need to consider rate limiting to prevent abuse
- Session duration is important for UX
### Next Action
Will research email service providers (Resend, SendGrid) and evaluate
their free tiers since budget constraint mentioned "no paid APIs".
---
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.
- 2d ago First seen · 301 lines · 22 tokens per session scan A 99b6a0e35901
observability is a skill published in the GitHub repository YougLin-dev/Aha-Loop (181 stars, last pushed 7mo ago), licensed MIT. It adds 22 tokens to every session and 1,581 once invoked, about $0.0001 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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