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 mishahanin/heading-os --skill rfp-responsegit clone --depth 1 https://github.com/mishahanin/heading-osWrote 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/mishahanin/heading-os/rfp-response)<a href="https://agentmods.dev/skills/mishahanin/heading-os/rfp-response"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os/rfp-response/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/mishahanin/heading-os/rfp-response"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os/rfp-response.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 | $0.00090 | $0.01036 |
| Opus 5 | $0.00045 | $0.00518 |
| Sonnet 5 | $0.00018 | $0.00207 |
| Haiku 4.5 | $0.00009 | $0.00104 |
Grade A, and why
rfp-response 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RFP Response
Produce a structured response to a formal Request for Proposals or government tender.
Variables
client: [Organization name and country] deadline: [Submission deadline] rfp_context: [Summary of requirements, or paste the RFP document below]
[PASTE RFP DOCUMENT OR REQUIREMENTS HERE]
Instructions
Before drafting, read:
context/business-info.md— ODUN.ONE modules, use case library, technical specifications, company credentialsreference/dpi-market-intelligence.md— Market positioning and certificationsreference/billion-growth-playbook.md— Pricing modelcontext/strategy.md— Competitive positioningcontext/current-data.md— Proof points (flagship deployment, patent filings, Tribe metrics)
Phase 1: Requirements Analysis
Map each stated requirement to ODUN.ONE capabilities:
| Requirement | Module/Use Case | Notes |
|---|---|---|
| [Req 1] | [DataONE / ControlONE / etc.] | [Full/partial compliance, notes] |
Identify:
- Where we're fully compliant (highlight)
- Where we need clarification
- Any requirements where we exceed expectations
Phase 2: Executive Summary
Draft a compelling 1-page executive summary that:
- Opens with why 31C is uniquely positioned for this opportunity
- Emphasizes sovereignty architecture (data never leaves sovereign control)
- References the flagship deployment as proof of production readiness
- States our commitment to this client's long-term success (Partnership for Life)
Phase 3: Technical Response
For each requirement:
- Solution description (which module and use case)
- How it meets the requirement
- Any relevant technical specifications
- Deployment model (on-premises, sovereign architecture)
Phase 4: Company Credentials
- 31C: Cybersecurity company, multi-site HQ, [N]+ Tribe members
- ODUN.ONE: Production deployment in [region] ([date])
- Partner ecosystem: distribution partners ([N]+ dealers), strategic technology alliance
- Research Lab: PhDs in quantum physics, AI/ML, mathematics, cryptography; 1 patent filed
- Hiring standard: 1,500+ interviews for ~20 hires
What ships with it
1 file 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 · 132 lines · 90 tokens per session scan A 6a3f15d96380
rfp-response is a skill published in the GitHub repository mishahanin/heading-os (11 stars, last pushed 3d ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,036 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
shogun-bloom-config
An interactive wizard that creates model-routing settings from your AI subscription choices. Model routing decides which available model handles each kind of task.
shogun-screenshot
A screenshot tool for getting images from a computer or web page and then cropping, resizing, or masking sensitive information. Playwright is a browser-automation tool used here to capture web pages.
shogun-model-list
A reference table of AI command-line tools, their available models, subscription requirements, and maximum Bloom capability levels. Bloom's Taxonomy is a scale describing thinking tasks, from remembering information to creating new designs.
shogun-model-switch
A live-switching tool for changing which command-line AI agent, model, and reasoning mode is running. It updates settings, restarts the agent, and refreshes the displayed session information.
shogun-readme-sync
A skill that compares an English README with its Japanese counterpart and brings them back into alignment. A README is the project document that explains what the software is and how to use it.
shogun-agent-status
A skill that shows whether the agents in a multi-agent Japanese feudal-themed team are working, waiting, missing, or assigned tasks. It combines terminal session status, task files, and unread messages.