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 skills/evoclaw/amplify/venue-alignmentnpx skills add EvoClaw/amplify --skill venue-alignmentgit clone --depth 1 https://github.com/EvoClaw/amplifyWrote 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/evoclaw/amplify/venue-alignment)<a href="https://agentmods.dev/skills/evoclaw/amplify/venue-alignment"><img src="https://agentmods.dev/badge/skills/evoclaw/amplify/venue-alignment.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.00731 |
| Opus 5 | $0.00018 | $0.00365 |
| Sonnet 5 | $0.00007 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
venue-alignment 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 5d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Venue Alignment (Meta-Control Layer)
Overview
A project that meets Tier C standards but targets a Tier A venue will be rejected. A project that exceeds Tier A standards but targets a Tier C venue wastes effort. This skill keeps project ambition and execution aligned with the target venue at every stage.
Check venue alignment at every gate and periodically during Phase 4 execution.
Gate-Specific Checks
G1 — Direction Validated
"Is the identified gap significant enough for [venue]?"
- Compare the claimed gap against recent publications at the target venue
- A gap that is incremental for Tier A may be sufficient for Tier B
- If gap is insufficient → warn user, suggest venue adjustment
G2 — Plan Frozen
"Does the method/analysis design have enough depth for [venue]?"
- Count innovation points, analysis dimensions, planned contributions
- Compare depth against accepted papers at the target venue
- If design is shallow for the target tier → warn user before freezing
G3 — Experiments Complete
"Is the planned experiment scale sufficient for [venue]?"
- Check baseline count, dataset count, ablation coverage, statistical rigor
- Compare against the venue tier requirements table below
- If scale falls short → warn user, suggest scaling up or adjusting venue
G4 — Paper Ready
"Does the evidence package (figures, tables, statistics) meet [venue] standards?"
- Count figures, tables, statistical tests, ablation studies
- Check completeness against the venue tier requirements
- If evidence is thin → warn user before submission
Venue Tier Requirements Reference
| Requirement | Tier A | Tier B | Tier C |
|---|---|---|---|
| Baselines | 5–8 strong, recent | 3–5 | 2–3 |
| Datasets | 3–5 | 2–3 | 1–2 |
| Ablation | Full component ablation | Key components | Optional |
| Statistics | CI + significance test | mean ± std | mean ± std |
| Novelty | Clear, significant advance | Solid contribution | Incremental or applied |
| Analysis depth | Multi-angle, comprehensive | Adequate coverage | Focused |
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.
- 5d ago First seen · 85 lines · 36 tokens per session scan A 90412821c22b
venue-alignment is a skill published in the GitHub repository EvoClaw/amplify (12 stars, last pushed 6mo ago), licensed MIT. It adds 36 tokens to every session and 731 once invoked, about $0.0002 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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