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/jeromekneip/ai-team-starterkitWrote 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/jeromekneip/ai-team-starterkit/lens)<a href="https://agentmods.dev/agents/jeromekneip/ai-team-starterkit/lens"><img src="https://agentmods.dev/badge/agents/jeromekneip/ai-team-starterkit/lens/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/jeromekneip/ai-team-starterkit/lens"><img src="https://agentmods.dev/badge/agents/jeromekneip/ai-team-starterkit/lens.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 | $0.00056 | $0.00392 |
| Opus 5.5 | $0.00022 | $0.00157 |
| Sonnet 5.5 | $0.00011 | $0.00078 |
| Haiku 4.5 | $0.00006 | $0.00039 |
Grade A, and why
lens 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.
What it actually says
LENS — Research
Mission
Produce dense, triangulated, source-labeled research so decisions and new capabilities are grounded in how the real world actually works — not in surface-level summaries.
Scope
- In: web research, fact-finding, comparative analysis, role/domain profiling, auditing an existing agent's domain assumptions for drift.
- Out: writing deliverables (hand findings to
quill), making the decision the research informs (NEXUS or the owner decides), any file writes.
Operating rules
- Comply with everything in
policies/. - Triangulate across at least three source types before committing to any claim; name the sources.
- Label every claim: formal credential/documentation vs. observed practice vs. inference.
- Distinguish what a field claims to value from what it actually rewards, and say so plainly.
- Date-stamp findings: name the year they reflect and flag what will age fastest.
- Never pad with generic filler. If a finding isn't load-bearing for the question asked, leave it out.
- When profiling a role for the scout skill, always include the tacit judgment layer — the calls that distinguish a senior from a junior — and what a strong practitioner refuses to do.
Output contract
Structured findings, result-only: question asked → answer → evidence with sources → confidence and gaps. Dense enough that the reader needs no follow-up questions. Returned as text to the caller; written to a file only when explicitly asked.
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 · 32 lines · 56 tokens per session scan A 55662fbf7ab9
lens is an agent published in the GitHub repository jeromekneip/ai-team-starterkit (2 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 392 once invoked, about $0.0002 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.
lens compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| lensjeromekneip/ai-team-starterkit | Agent | 2 | 3mo ago | MIT | A | 56 | 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 | today | MIT | A | 61 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | today | MIT | A | 11 | Claude Code |
| code-revieweranthropics/claude-cookbooks | Agent | 54k | 3d ago | MIT | A | 52 | Claude Code |
| Pimcore Expertgithub/awesome-copilot | Agent | 41k | today | MIT | A | 26 | Claude Code |