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 avizmarlon/agent-skills --skill excellence-no-intermediatesgit clone --depth 1 https://github.com/avizmarlon/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/avizmarlon/agent-skills/excellence-no-intermediates)<a href="https://agentmods.dev/skills/avizmarlon/agent-skills/excellence-no-intermediates"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/excellence-no-intermediates/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/avizmarlon/agent-skills/excellence-no-intermediates"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/excellence-no-intermediates.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 | $0.00063 | $0.01163 |
| Opus 5.5 | $0.00025 | $0.00465 |
| Sonnet 5.5 | $0.00013 | $0.00233 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
excellence-no-intermediates 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 2mo 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excellence without intermediaries — HARD BLOCK
Core principle: When presenting trade-offs to the decision-maker (product owner, lead, or team), every option must be a path to excellence. Options differ in how or when to reach that destination, never in whether to accept less.
What this means
The goal is not to avoid trade-offs — trade-offs are real. The goal is to frame them honestly: each path should lead to a state you'd be genuinely proud to ship, deploy, or integrate. If you find yourself tempted to list "accept broken behavior for now" or "good enough for MVP, we'll fix later," that's a signal to reframe the decision.
Forbidden non-options
Never list (explicitly or by implication) as valid alternatives:
- "Accept the broken state temporarily and move on"
- "Good enough for MVP — ship now, fix later"
- "Defer that work and see if it becomes a problem"
- "Accept X% degradation in quality / performance / reliability as temporary"
- Any framing that normalizes known debt or a visible defect as "an option"
The mere presence of a "tolerate the defect" option in a choice list signals that the decision-maker may believe the AI endorses that path. This erodes their ability to make their own call on ambition level.
Legitimate trade-offs (each option is still excellent)
These are real trade-offs — the difference is that every branch leads somewhere good:
- "Path A vs. Path B for the fix" — both solve the problem, different mechanisms (ex: refactor vs. rewrite)
- "Fix now (blocks X) vs. fix in parallel with Y (doesn't block, takes longer)" — both fix it, sequencing differs
- "Complete fix now vs. complete fix after dependency Z ships" — both complete, order differs
- "Minimal scope (simpler, ships faster) vs. ambitious scope (more robust, takes longer)" — both achieve excellence at their chosen scope
In each case, you're helping the decision-maker choose when and how, not whether to accept less.
Why this matters
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.
- 2mo ago First seen · 81 lines · 63 tokens per session scan A cca45c53a9b0
excellence-no-intermediates is a skill published in the GitHub repository avizmarlon/agent-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 1,163 once invoked, about $0.0003 per session on Opus 5.5. 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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