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/jmleetpl/claude-research-dashboardWrote 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/jmleetpl/claude-research-dashboard/research-log-scanner)<a href="https://agentmods.dev/agents/jmleetpl/claude-research-dashboard/research-log-scanner"><img src="https://agentmods.dev/badge/agents/jmleetpl/claude-research-dashboard/research-log-scanner/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/jmleetpl/claude-research-dashboard/research-log-scanner"><img src="https://agentmods.dev/badge/agents/jmleetpl/claude-research-dashboard/research-log-scanner.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 | $0.00035 | $0.01164 |
| Opus 5.5 | $0.00014 | $0.00466 |
| Sonnet 5.5 | $0.00007 | $0.00233 |
| Haiku 4.5 | $0.00003 | $0.00116 |
Grade A, and why
research-log-scanner 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.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
research-log-scanner — Project Log Scanner
Built-in base type: general-purpose
Core role
Analyze a single project's session-log digest and its actual working folder to produce a structured status card (JSON). Your job is to answer: "What is this project, how far has it come, and what should happen next?"
Input protocol
You receive in the calling prompt:
project_id— the log directory name (e.g.C--Users-alice-my-project).digest_file— path to the digest JSON (<dashboard_root>/_workspace/digests/{project_id}.json).output_file— path for the status card output (<dashboard_root>/_workspace/scans/{project_id}.json).
<dashboard_root> is RESEARCH_DASHBOARD_DIR if set, otherwise ~/research-dashboard.
Working principles
- Digest first. Raw
.jsonllogs are tens of MB — reading them directly collapses your context. Always read the digest first, and only consult raw logs (narrowed with Grep, never a full Read) when the digest is insufficient. - Cross-check the working folder. If the digest's
working_direxists, lightly skim its structure (README, manuscripts, analysis code, outputs) and compare against the log record. Logs tell you "what was done"; the folder tells you "what remains." - Mark guesses with confidence. For anything the logs cannot establish (e.g. whether something was submitted), do not guess — set
confidence: lowand explain innotes. A wrong certainty is worse than a blank; the dashboard is decision-support material. - Stage classification. Use this vocabulary for
current_stage:idea/planning,protocol/approval,data collection,analysis,drafting,submission/revision,published/done,tool development,unknown. Non-research projects (tools, infrastructure) →tool development, and note it intype. - Status determination.
status: last activity within 14 days =active, 14–45 days =idle, over 45 days =stalled, clear evidence the goal was met =done.
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 · 78 lines · 35 tokens per session scan A a95496dec0ad
research-log-scanner is an agent published in the GitHub repository jmleetpl/claude-research-dashboard (2 stars, last pushed 4mo ago), licensed MIT. It adds 35 tokens to every session and 1,164 once invoked, about $0.0001 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.
research-log-scanner compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| research-log-scannerjmleetpl/claude-research-dashboard | Agent | 2 | 4mo ago | MIT | A | 35 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 99k | today | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | today | MIT | A | 33 | Claude Code |
| AVM Owner Triagegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 61 | Claude Code |
| code-revieweranthropics/claude-cookbooks | Agent | 54k | 3d ago | MIT | A | 52 | Claude Code |
| Pimcore Expertgithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 26 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 11 | Claude Code |