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 Gerg/ai_agent_skills --skill technical-proposal-craftinggit clone --depth 1 https://github.com/Gerg/ai_agent_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/gerg/ai_agent_skills/technical-proposal-crafting)<a href="https://agentmods.dev/skills/gerg/ai_agent_skills/technical-proposal-crafting"><img src="https://agentmods.dev/badge/skills/gerg/ai_agent_skills/technical-proposal-crafting/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/gerg/ai_agent_skills/technical-proposal-crafting"><img src="https://agentmods.dev/badge/skills/gerg/ai_agent_skills/technical-proposal-crafting.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 | $0.00128 | $0.02302 |
| Opus 5 | $0.00064 | $0.01151 |
| Sonnet 5 | $0.00026 | $0.00460 |
| Haiku 4.5 | $0.00013 | $0.00230 |
Grade A, and why
technical-proposal-crafting 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Proposal Skill
Write, review, and edit design proposals that drive alignment (HLD) and guide implementation (LLD).
When using this skill, begin by stating: "I'm using the technical-proposal-crafting skill, which enforces: right altitude for the audience, a narrative that builds a case rather than filing a report, each fact stated once, explicit status tagging (IMPLEMENTED/WIRING-ONLY/NET-NEW), and confident voice throughout."
Context: This skill covers writing, reviewing, and editing both High-Level and Low-Level design proposals across any domain. For document-type specifics, read references/hld.md and references/lld.md. For the discipline of grounding claims, read references/claim-grounding.md. Read references on demand.
Core Principles
- Pick the right altitude first. HLD ≠ LLD ≠ both-in-one. An HLD aligns stakeholders on boundaries, contracts, and decisions; an LLD documents mechanics for implementers. Mixing them produces a doc that is too detailed for approvers and too vague for engineers. Decide which you're writing (or write both, cleanly separated) before drafting. See
references/hld.md/references/lld.md. - Build a case, not a report. The document should read as a logical progression: here is the problem, here is the solution, here is why it works. Each section should earn its place by advancing the argument, not by checking a structural box. If a section's content would be equally true in any order, the narrative has no arc.
- State each fact once. If a fact needs to appear in two sections, one of those sections has a structural problem. Restate it once (in the most authoritative location) and rely on the reader's memory for the rest. Repetition signals the author didn't trust the document's structure — and signals an AI generator padding for completeness.
- Write confidently. An HLD should only be written once key decisions are settled. Hedged language — "should be confirmed by X," "may need to revisit" — signals the document is premature. Resolve the open questions first. If a scope boundary genuinely can't be resolved at HLD time, state it explicitly as a non-goal or downstream concern; don't leave it as an inline hedge.
- Ground load-bearing claims in verifiable sources. A design that asserts "component X exposes port Y / requires permission Z / already does W" must be checkable against code, config, or a cited doc. Ungrounded specifics are a common cause of proposals that pass review and then fail in implementation. See
references/claim-grounding.md. - Tag implemented and proposed; don't rely on tense. Mark every behavioral claim explicitly: IMPLEMENTED (in source today), WIRING-ONLY (needs config/flag), NET-NEW (must be built). Tense is a readability choice; it does not reliably distinguish what exists from what must be built. See
references/claim-grounding.md. - No fact drift across linked documents. When an HLD points to an LLD, a fact stated in both must match exactly. Correct a claim in one place and the contradiction is a defect. Keep numbers, names, and permissions single-sourced.
- State what you deliberately did NOT do. Non-goals prevent re-litigating settled questions. Rejected alternatives are optional (an appendix is the right home) — but scope boundaries belong in the HLD body.
- Write for the document's actual audience. An HLD a PM cannot follow has failed regardless of technical merit. An LLD that hand-waves the mechanics has failed the engineer. Match vocabulary and depth to who must act on the doc.
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 · 93 lines · 128 tokens per session scan A f54cdab3eb28
technical-proposal-crafting is a skill published in the GitHub repository Gerg/ai_agent_skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 128 tokens to every session and 2,302 once invoked, about $0.0006 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.
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