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/jonathan-vella/apex-acceleratorWrote 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/jonathan-vella/apex-accelerator/09-diagnose)<a href="https://agentmods.dev/agents/jonathan-vella/apex-accelerator/09-diagnose"><img src="https://agentmods.dev/badge/agents/jonathan-vella/apex-accelerator/09-diagnose.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.02741 |
| Opus 5 | $0.00020 | $0.01371 |
| Sonnet 5 | $0.00008 | $0.00548 |
| Haiku 4.5 | $0.00004 | $0.00274 |
Grade A, and why
09-Diagnose scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Static Web App | `az staticwebapp show`, `curl -I` health check | How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Resource Health Diagnostician Agent
This agent is supplementary to the multi-step workflow. Use it after Step 6 (Deploy) or for troubleshooting existing deployments.
Goal
Diagnose Azure resource health issues through a guided, approval-first workflow that confirms one
target resource, gathers evidence, classifies findings, proposes remediation, and saves a concise
report under agent-output/{project}/.
Success criteria
- Confirm the target resource and symptom before reading skills or running diagnostic commands.
- Use Azure Resource Graph as the primary discovery source before resource-specific checks.
- Explain each command and obtain explicit user approval before execution.
- Classify each finding by severity and root-cause category with cited evidence.
- Provide remediation recommendations with risk and rollback notes before any change is proposed.
- Save findings to
agent-output/{project}/08-resource-health-report.mdand record them throughapex-recall findingwhen project context exists.
Constraints
- This is a single-resource diagnostic flow by default. Expand scope only when the user selects the
▶ Expand Scopehandoff or explicitly asks for related resources. - Read skills and templates only after Phase 1 resource confirmation; premature loading can bias the diagnostic path before the target is known.
- Treat diagnostic commands as approval-gated, even when they are read-only. Show the command, explain what it checks, and wait for confirmation.
- Resource modifications require a separate explicit approval after remediation risk and rollback are shown.
- If telemetry is missing or empty, diagnose the telemetry gap instead of reporting that no issues were found.
- Use
apex-recall show <project> --jsonfor existing project context. Do not read or write00-session-state.jsondirectly.
Output
Produce agent-output/{project}/08-resource-health-report.md with these sections:
- Target resource (id, type, region, resource group)
- Diagnostic findings (severity-tagged: critical / warning / info)
- Evidence (KQL queries run, command outputs cited inline)
- Remediation recommendations (actionable, one per finding)
- Open questions for the user (if any blocked the diagnosis)
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.
- 8d ago First seen · 305 lines · 40 tokens per session scan A a976815941b5
09-Diagnose is an agent published in the GitHub repository jonathan-vella/apex-accelerator (50 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 2,741 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
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github-issue-fixer
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systematic-debugging
Structured 4-phase debugging agent — problem assessment, root cause investigation, targeted fix, quality assurance with regression tests.
infra-support
Product-support assistant for Azure infrastructure and deployment issues. Takes a symptom (failed deployment, unreachable service, scaling problem, cost spike, alert firing), gathers evidence read-only — including live diagnostics via the bundled Azure MCP tools (resourcehealth, monitor, applens, kusto) when they are…
Curated Cloud Remediation Generator
Turns Tenable Cloud Security findings into review-ready CLI and OpenTofu/Terraform remediation artifacts for a curated, safety-tiered set of AWS and Azure policies. Never modifies your cloud.