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 Neetx/ai-research-radar --skill radar-source-healgit clone --depth 1 https://github.com/Neetx/ai-research-radarWrote 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/neetx/ai-research-radar/radar-source-heal)<a href="https://agentmods.dev/skills/neetx/ai-research-radar/radar-source-heal"><img src="https://agentmods.dev/badge/skills/neetx/ai-research-radar/radar-source-heal/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/neetx/ai-research-radar/radar-source-heal"><img src="https://agentmods.dev/badge/skills/neetx/ai-research-radar/radar-source-heal.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 | $0.00104 | $0.01762 |
| Opus 5.5 | $0.00042 | $0.00705 |
| Sonnet 5.5 | $0.00021 | $0.00352 |
| Haiku 4.5 | $0.00010 | $0.00176 |
Grade A, and why
radar-source-heal 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 7d 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 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.
- 7d ago Changed · +19 lines 1a7d9aa46a10
- 1mo ago First seen · 103 lines · 104 tokens per session scan A 3de2f0349119
radar-source-heal is a skill published in the GitHub repository Neetx/ai-research-radar (4 stars, last pushed yesterday), with no licence file. It adds 104 tokens to every session and 1,762 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
property-repro
Reproduce a reported Honcho API bug (a 5xx, a wrong status code, data that doesn't round-trip) as a failing Hypothesis/Schemathesis test, then fix it. Use when an issue reports an unexpected API error, when hunting for 5xx bugs in a route, or before changing request validation or error handling.
honcho-cli
Inspect and debug Honcho workspaces via the honcho CLI. Use when investigating peer representations, memory state, session context, or dialectic quality — any task that requires introspection of a Honcho deployment, including verifying that a recall/record memory loop is actually working.
troubleshooting
Diagnoses and repairs core-memory-kit itself when the memory system is broken — the per-failure-code repair book. Fire whenever a "⚠ [core-memory-kit]" whisper appears on the prompt (it names the failure and points here), or when the user reports a kit symptom however they phrase it: memory is not being saved, nothing…
debug-with-memlog
Systematically investigate bugs, errors, test failures, build failures, deployment failures, regressions, performance problems, and unexpected behavior with prior Memlog lessons. Use before proposing fixes, especially after a previous fix failed.
pre-action-interceptors
Use when a tool error begins with "INTERCEPTOR:", a sent message was silently hedged or rewritten, or the user asks about active guards or blocked actions. Not for ordinary tool errors.
observability
Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices). On a real anomaly, open a bug task (--kind workitem) carrying the evidence refs so it re-enters the bugfix loop. A healthy sweep opens NO task — never fabricate a bug.