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 whaojie797-design/Novera-AI-skills --skill agentic-debuggergit clone --depth 1 https://github.com/whaojie797-design/Novera-AI-skillsWrote 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/whaojie797-design/novera-ai-skills/agentic-debugger)<a href="https://agentmods.dev/skills/whaojie797-design/novera-ai-skills/agentic-debugger"><img src="https://agentmods.dev/badge/skills/whaojie797-design/novera-ai-skills/agentic-debugger/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/whaojie797-design/novera-ai-skills/agentic-debugger"><img src="https://agentmods.dev/badge/skills/whaojie797-design/novera-ai-skills/agentic-debugger.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 | $0.00092 | $0.00711 |
| Opus 5.5 | $0.00037 | $0.00284 |
| Sonnet 5.5 | $0.00018 | $0.00142 |
| Haiku 4.5 | $0.00009 | $0.00071 |
Grade A, and why
agentic-debugger 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
4 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.
- 2mo ago First seen · 85 lines · 92 tokens per session scan A bfaaa40bfc05
agentic-debugger is a skill published in the GitHub repository whaojie797-design/Novera-AI-skills (2 stars, last pushed 3mo ago), with no licence file. It adds 92 tokens to every session and 711 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 2026-08-31.
Other skills, from other repositories
api-analyzer
Validates whether an API request is correct based on provided inputs (method, URL, headers, body, auth, query params).
agent-harness-fault-injection
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
agent-observability
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
ai-sre-incident-response
Build AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety regressions.
api-integration-architect
Design, implement, debug, and optimize API integrations with expert-level patterns for REST, GraphQL, webhooks, and authentication flows.
agent-qa-debug-fix
Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.