Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
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 daymade/claude-code-skills --skill benchmark-due-diligencegit clone --depth 1 https://github.com/daymade/claude-code-skillsWrote 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/daymade/claude-code-skills/benchmark-due-diligence)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/benchmark-due-diligence"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/benchmark-due-diligence/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/daymade/claude-code-skills/benchmark-due-diligence"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/benchmark-due-diligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00181 | $0.02246 |
| Opus 5 | $0.00090 | $0.01123 |
| Sonnet 5 | $0.00036 | $0.00449 |
| Haiku 4.5 | $0.00018 | $0.00225 |
Grade A, and why
benchmark-due-diligence 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 9d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Due Diligence
Take a benchmark the user envies — a founder, KOL, company, or product whose success looks suspiciously shiny — and produce a teardown that ends in "what this means for ME", not a neutral report. The deliverable answers three questions a balanced briefing never does: How much of this success is real vs marketing bubble? How much is replicable method vs luck/timing? And what, specifically, can the commissioner do with it?
This is the adversarial, decision-oriented cousin of deep-research. Where deep-research builds a trustworthy picture of the world, this skill assumes the picture is inflated until proven otherwise and converts the survivors into the commissioner's own moves.
CRITICAL: run inline, never context: fork
This skill is an orchestrator — it spawns parallel collection + verification agents (via the Workflow tool, or Task agents) and may invoke other skills (deep-research, osint-investigate, qcc). Subagents cannot spawn subagents or call skills. Setting context: fork would silently break the entire fan-out. Do not add a context field. (Same constraint osint-investigate documents — it's a hard runtime rule, not a preference.)
The one rule that protects the commissioner: two injection channels
Everything the agents see flows through exactly two channels. Keeping them separate is the single most important discipline in this skill:
| Channel | Content | Injected into |
|---|---|---|
| FACTS | Already-verified public facts about the benchmark (relationships, who-owns-what, the headline claim flagged ⚠️ to-verify) |
Every agent — collection, verification, synthesis |
| COMMISSIONER_CONTEXT | The commissioner's private reality — real resources, client names, strategic intent, what they can actually leverage | Only the final mapping agent (Phase 4) |
Why this split is non-negotiable: collection and verification agents take their input and run external WebSearch on it. If the commissioner's client names or strategy leak into those prompts, they get searched on the open web — a privacy breach. The mapping phase genuinely needs "who is the commissioner"; the collection phase must never see it. Encode this in the orchestration (see references/workflow_orchestration_template.md), don't rely on remembering it mid-run.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 110 lines · 181 tokens per session scan A b4e58ad49d07
benchmark-due-diligence is a skill published in the GitHub repository daymade/claude-code-skills (1,384 stars, last pushed today), licensed MIT. It adds 181 tokens to every session and 2,246 once invoked, about $0.0009 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 2026-08-30.
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