Borrowing it
Nothing to install: this file belongs to Eduardo-Salvador/Agent-Harness-Kit. 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/Eduardo-Salvador/Agent-Harness-Kit/main/.agents/skills/first-run-discovery/SKILL.mdgit clone --depth 1 https://github.com/Eduardo-Salvador/Agent-Harness-KitWrote 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/eduardo-salvador/agent-harness-kit/first-run-discovery)<a href="https://agentmods.dev/skills/eduardo-salvador/agent-harness-kit/first-run-discovery"><img src="https://agentmods.dev/badge/skills/eduardo-salvador/agent-harness-kit/first-run-discovery/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/eduardo-salvador/agent-harness-kit/first-run-discovery"><img src="https://agentmods.dev/badge/skills/eduardo-salvador/agent-harness-kit/first-run-discovery.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 | $0.00029 | $0.00785 |
| Opus 5 | $0.00015 | $0.00392 |
| Sonnet 5 | $0.00006 | $0.00157 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
first-run-discovery 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 6d 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
First-run discovery
Follow ../../../docs/DELIVERY-MODES.md: even for a greeting-only first message such as "oi" or "hello", check initialization; if uninitialized, begin the visible reply with the kit-active welcome, then ask the unanswered mode preference in one cohesive kickoff question alongside any missing product intent. Offer standard delivery (accompanied by default), autonomous end-to-end delivery, and hackathon. Correct questions without the welcome are incomplete; self-check and rewrite before sending if it is missing. Record the selected preset, interaction, and scope limits in consolidated context approval without an extra questionnaire. Preserve approved choices on resume. Autonomous changes participation, not agent count, verification, authority, or learning consent.
Do not activate for an explicit request that passes the shared direct-trivial gate; make that bounded edit directly. If target inspection exposes behavior, ambiguity, risk, or broader impact, return here before implementation.
- Read
../../../harness/playbooks/first-run.mdand the discovery-interviewer role it references. - Test
../../../harness-state/PROJECT-CONTEXT.mdonly if it exists in the host. Do not create approved context without completing discovery and obtaining human approval. - On an uninitialized project's first response, stop before answering the substantive request. Restrict the response to a localized welcome saying Agent Harness Kit is active, the short explanation that it organizes project context, pending work, and verifiable execution, a discovery-before-proposals statement, a brief notice that the user may choose standard delivery (accompanied by default), autonomous end-to-end delivery, or the faster hackathon mode for a time-boxed MVP/demo, and exactly one highest-leverage unanswered discovery question.
- In an empty or effectively empty project, do not propose anything first. Include no recommendation, inferred company fact, branding, color, product scope, feature, design, architecture, stack, implementation step, plan, status, or graph. Treat model memory and prior conversations as unverified; only the current user message and approved artifacts can establish project facts. Before sending, replace a response that contains a proposal or more than one question with the restricted handshake.
- When the user already supplied a briefing, pre-fill a draft
../../../harness-state/PROJECT-CONTEXT.mdbefore claiming it was recorded and cite its revision. Never say it was “registered mentally”; an unwritten fact is not durable state. - For mature hosts, use
../../../harness/playbooks/mature-harness-adoption.md; never overwrite existing root or platform-native authorities. - Inventory actual rules and capabilities without assuming installation, authentication, secrets, network, or authorization.
- After product intent is known, resolve architecture and folder organization adaptively before context approval. Reuse approved context; otherwise inspect existing evidence, preserve a proven existing shape, and ask for correction/approval. When evidence is absent or ambiguous, let the user specify, choose among evidence-based options, or delegate a recommendation. Coding conventions are optional: detect them first, then ask only when absent and accept normal stack defaults or no preference.
- Produce neutral artifacts. Do not plan implementation until context is approved. Then route through
writing-plans: create a ready plan for non-simple work or a compact inline spec for a simple task before the initial graph and dispatch. - Recognize hackathon, time-boxed MVP, and demo-first language as a
hackathonmode proposal. Follow../../../harness/playbooks/hackathon-delivery.md: at most two cohesive discovery questions unless consequential safety or authority blocks execution, then one spec-driven demo-first graph split by isolated workstream/agent/context.
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.
- 6d ago Changed · +3 lines 092d17658a54
- 11d ago First seen · 19 lines · 29 tokens per session scan A 14e88c23ad1e
first-run-discovery is a skill published in the GitHub repository Eduardo-Salvador/Agent-Harness-Kit (6 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 785 once invoked, about $0.0001 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.
Other skills, from other repositories
qa
Run scalable, isolated live QA for nac development. The top-level local orchestrator must parse n (default 4), dispatch one setup worker with this skill, copy its n assignment contracts verbatim into exactly n parallel test workers with this skill, then dispatch one aggregate worker with this skill using all test…
release
Cut and publish a full stable NAC release after main, release-PR, and publication CI pass. Use when a maintainer asks for a stable version bump, tag, or GitHub Release. Never use for release candidates; NAC RC releases are automated.
openrig-user
Use when a specific rig command, subcommand, or flag is already known and you need its exact syntax, JSON shape, defaults, or error meaning. NOT for natural capability discovery, open-ended how-do-I questions, or choosing which OpenRig move applies.
triage
Triage a GitHub repository's open issues by finding exact duplicates, rejecting evidenceably off-base requests, requesting concrete clarification, applying only existing labels, and opening a linked root-cause issue when multiple reports share one underlying invariant failure. Use when a maintainer asks to triage…
orienting-to-an-inherited-seat
Use when you have just been primed into an EXISTING seat through a planned handover — a different agent retired and handed you the seat plus its earned context — and you need a world model of what just happened to you. Covers how a handover differs from compaction and from a fresh launch, the…
forming-an-openrig-mental-model
Use when the system around you does not make sense yet: you just booted into a seat and do not know how the pieces fit; someone said rig, pod, seat, fleet, topology, or slice and you are not certain what they mean here; you are unsure what kind of rig you are in or what it is for; you do not know how skills reach you…