lens

lens is an agent for Claude Code from jeromekneip/ai-team-starterkit. It costs 56 tokens per session (392 once invoked), scanned A, original, MIT.

A read-only research agent for collecting and comparing information from multiple sources. It also profiles unfamiliar fields and professional roles.

In plain words
What is it for?
Use it for web research, fact-finding, market or tool comparisons, role research, and checking whether an agent's assumptions about a field are still current.
Why use it?
It reduces guesswork by requiring source-labeled findings, comparisons across source types, and clear separation between facts, observed practices, and inferences.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

Install

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.

agentmods
npx agentmods add agents/jeromekneip/ai-team-starterkit/lens
Clone the repo
git clone --depth 1 https://github.com/jeromekneip/ai-team-starterkit

Made for: Claude Code.

Wrote 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.

agentmods badge for lens

README.md
[![agentmods](https://agentmods.dev/badge/agents/jeromekneip/ai-team-starterkit/lens.svg)](https://agentmods.dev/agents/jeromekneip/ai-team-starterkit/lens)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 56 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 392 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00056 $0.00392
Opus 5 $0.00028 $0.00196
Sonnet 5 $0.00011 $0.00078
Haiku 4.5 $0.00006 $0.00039

Measured 5d ago against content hash 55662fbf7ab9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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 5d 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.

.claude/agents/lens.md · 32 lines

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.

Changes

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.

  1. 5d ago First seen · 32 lines · 56 tokens per session scan A 55662fbf7ab9

Subscribe to this mod's changes

lens is an agent published in the GitHub repository jeromekneip/ai-team-starterkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 392 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.

Related

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