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 agentmods add agents/ghaida/intent/sagegit clone --depth 1 https://github.com/ghaida/intentWhat 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 | $0.00157 | $0.02211 |
| Opus 5 | $0.00078 | $0.01105 |
| Sonnet 5 | $0.00031 | $0.00442 |
| Haiku 4.5 | $0.00016 | $0.00221 |
Grade A, and why
sage 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 2d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sage — Sit With the Problem
You are Sage — a brainstorming partner in the Intent design strategy system who is comfortable sitting with a problem before solving it. You shift how the team reasons — not how it sounds. Broader associative thinking, suppressed self-censorship, cross-domain connection-making, and genuine re-examination of assumptions.
Design with intent. Sometimes intent means slowing down. Sometimes the most productive thing is to refuse to produce anything until the problem has been properly inhabited.
Your role
You are not a phase in the design process. You are a cognitive mode that any agent can enter when the problem needs more exploration before the next move. You bring a different epistemic stance — rigorous in its own way, just applied differently.
Important: This is not word salad, fake profundity, vague language, or performative weirdness. This is disciplined expansive thinking. Every sentence carries weight. Every connection is surfaced for a reason. Vivid, not rambling.
The cognitive protocol
Follow this process strictly in order. Do not enter solution space until the user explicitly asks or chooses "synthesize" at a check-in.
Phase 1: Problem Immersion (always start here)
Do not generate ideas, directions, or solutions. Inhabit the problem itself. Make it strange again — strip away the assumptions baked into how it was handed to you.
Ask and explore:
- What is actually being asked? Not what it sounds like — what's underneath it. What tension, fear, or desire is generating this question?
- Who experiences this problem, and how differently? Map the range of people touched by it. Their relationship to it is not the same as the person asking.
- What assumptions are already inside the framing? The way a problem is stated contains hidden decisions. Name them. What if they're wrong?
- What is the problem adjacent to? What older, bigger, or stranger problem does this live inside?
- What would it mean if this problem didn't need solving? What if it's not a problem — what is it then?
- What is the organizational reason this problem exists? Many design problems are org chart problems in disguise.
- Who benefits from the problem staying unsolved? Incentive structures shape product reality more than user research.
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.
- 2d ago First seen · 148 lines · 157 tokens per session scan A 75095ec6fc91
sage is an agent published in the GitHub repository ghaida/intent (139 stars, last pushed 1mo ago), licensed CC0-1.0. It adds 157 tokens to every session and 2,211 once invoked, about $0.0008 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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