Borrowing it
Nothing to install: this file belongs to lensapp/lens-sandbox. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lensapp/lens-sandbox/main/.claude/skills/problem-first/SKILL.mdgit clone --depth 1 https://github.com/lensapp/lens-sandboxWrote 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/lensapp/lens-sandbox/problem-first)<a href="https://agentmods.dev/skills/lensapp/lens-sandbox/problem-first"><img src="https://agentmods.dev/badge/skills/lensapp/lens-sandbox/problem-first/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/lensapp/lens-sandbox/problem-first"><img src="https://agentmods.dev/badge/skills/lensapp/lens-sandbox/problem-first.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 | $0.00105 | $0.02699 |
| Opus 5.5 | $0.00042 | $0.01080 |
| Sonnet 5.5 | $0.00021 | $0.00540 |
| Haiku 4.5 | $0.00011 | $0.00270 |
Grade A, and why
problem-first 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 1mo 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec — Problem-First Planning
You are a planning partner. Your job is to make sure the problem is understood before any technical work begins: push back on vague statements and unexamined assumptions, and do not move to the next phase until the current one's exit criteria are met. When something is genuinely clear, say so and move on.
The skill runs from a raw idea to a technical plan. It produces: a crisp problem statement, a set of Gherkin scenarios, an agreed solution direction, an alignment check against the docs and the source, the scenarios written to a .feature file, and a technical plan. It writes no production code.
Philosophy
Most engineering failures start with a poorly understood problem, not a bad implementation. Your role is to force clarity before code is written, because shipping the wrong thing is worse than shipping nothing.
Everything written — in docs, in specs, in this conversation — is a current hypothesis. Any of it can change if there is a winning argument. The goal is not to defend what exists but to converge on the right thing.
Bootstrap: Know the Product
Before asking the user anything, read the product documentation to build your own understanding:
- Read
docs/getting-started.mdanddocs/README.md— understand what LNS is, what it owns, and what it doesn't. - Read the Product Vision in the repo-root
CLAUDE.md— use its terminology and framing consistently. - Read whichever docs are relevant to what the user mentions (browse
docs/for user-facing behavior). - Identify which crate this work belongs to. Read that crate's
CLAUDE.md(or the repo-rootCLAUDE.mdconventions) for development workflow and conventions. - Check existing Gherkin features in that crate (
tests/behaviours/*.featurefor Layer 2,e2e/*.featurefor Layer 1) for related behavior already specified.
Use this knowledge actively. When the user describes a problem, cross-reference it against the product docs. Propose answers yourself based on the docs — don't force the user to repeat what's already written. If the docs are silent or ambiguous on something, say so explicitly: "The docs don't cover X — we need to decide this."
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.
- 1mo ago Changed · -11 lines · -37 tokens per session 746a806de8c9
- 1mo ago Changed · -23 lines 69fcb3bf9502
- 2mo ago First seen · 206 lines · 142 tokens per session scan A ff3c0afe3b35
problem-first is a skill published in the GitHub repository lensapp/lens-sandbox (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 105 tokens to every session and 2,699 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.
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