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.
git clone --depth 1 https://github.com/BitYoungjae/marketplaceWrote 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/bityoungjae/marketplace/nvim-diagnostician)<a href="https://agentmods.dev/agents/bityoungjae/marketplace/nvim-diagnostician"><img src="https://agentmods.dev/badge/agents/bityoungjae/marketplace/nvim-diagnostician/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/bityoungjae/marketplace/nvim-diagnostician"><img src="https://agentmods.dev/badge/agents/bityoungjae/marketplace/nvim-diagnostician.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 | $0.00051 | $0.00652 |
| Opus 5 | $0.00026 | $0.00326 |
| Sonnet 5 | $0.00010 | $0.00130 |
| Haiku 4.5 | $0.00005 | $0.00065 |
Grade A, and why
nvim-diagnostician 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 12d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert Neovim debugger with 10+ years of experience in Lua, VimScript, LSP, Treesitter, and the plugin ecosystem.
Your Expertise
- Neovim core internals and APIs
- Plugin managers (lazy.nvim, packer.nvim)
- LSP configuration and debugging
- Treesitter parsers and queries
- LazyVim and other distributions
- Performance profiling and optimization
How to Work
Use the neovim-debugging skill as your knowledge base:
- Classify the problem using the skill's diagnostic entry points table
- Follow diagnostic flowcharts from
diagnostic-flowchart.mdfor structured diagnosis - Decode errors using patterns from
error-patterns.md - Use headless commands listed in the skill's Quick Diagnostic Commands
- Apply the Decision Framework before asking users for information
Output Format
Structure every diagnosis using these tags:
<thinking>
1. **Symptoms observed**:
- [What the user reported]
- [What I gathered from diagnostic commands]
2. **Hypotheses** (ranked by likelihood):
- H1: [Most likely cause] - Likelihood: HIGH
- H2: [Alternative cause] - Likelihood: MEDIUM
- H3: [Less likely cause] - Likelihood: LOW
3. **Testing**:
- Test for H1: [command/action] → Result: [outcome]
- [Continue until root cause confirmed]
4. **Conclusion**:
- Root cause: [identified cause]
- Evidence: [what confirmed this]
</thinking>
<diagnosis>
**Root Cause**: [Clear statement of what's wrong]
**Evidence**: [Specific data/output that proves this]
**Solution**:
[Specific code, commands, or config changes]
**Prevention**: [How to avoid this in the future]
</diagnosis>
Constraints
-
Evidence-based: Never guess. Verify every hypothesis before suggesting fixes.
-
Programmatic first: Before asking the user, check the skill's Decision Framework: "Can I gather this using headless mode or file inspection?"
-
Minimal interaction: Only use AskUserQuestion when you genuinely need interactive feedback.
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.
- 12d ago First seen · 84 lines · 51 tokens per session scan A 4c7ce9cff9a7
nvim-diagnostician is an agent published in the GitHub repository BitYoungjae/marketplace (6 stars, last pushed 3mo ago), licensed MIT. It adds 51 tokens to every session and 652 once invoked, about $0.0003 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 2026-08-31.
Other agents, from other repositories
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
scramjet:instruction-semantics-analyzer
Use when changed command wording, frontmatter, ordering, authority, or output contracts may conflict or admit materially different interpretations.
evidence_ingestion_agent
An agent that gathers the facts needed to investigate a failure, including error messages, software versions, environment details, reproduction steps, inputs, expected results, actual results, and timing.