Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/agents/endogenai/dogma/context-amplification-calibration)<a href="https://agentmods.dev/agents/endogenai/dogma/context-amplification-calibration"><img src="https://agentmods.dev/badge/agents/endogenai/dogma/context-amplification-calibration.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 5.1 | $0.00000 | $0.04227 |
| Opus 5 | $0.00000 | $0.02114 |
| Sonnet 5 | $0.00000 | $0.00845 |
| Haiku 4.5 | $0.00000 | $0.00423 |
Grade A, and why
context-amplification-calibration 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context-Sensitive Amplification Calibration: Task-Type Axiom Activation Effectiveness
Research question: Does explicit task-type-based axiom amplification (the AGENTS.md lookup table, Phase 1 implementation) produce measurable quality improvements in agent session outcomes? Can amplification weight ratios be calibrated per task type? Date: 2026-03-10 Closes: #178 Related:
docs/research/epigenetic-tagging.md§3 Pattern F1–F2;docs/research/values-encoding.md§5 OQ-VE-2;AGENTS.md §Context-Sensitive Amplification
1. Executive Summary
The context-sensitive amplification mechanism — an AGENTS.md lookup table mapping task-type keywords to the axiom that should be foregrounded at session start — was designed to address the regulatory-region gap identified in values-encoding.md §H5 and implemented in Phase 1 (2026-03-09). This synthesis provides empirical calibration evidence from analysis of ≥2 session records per task type.
Corpus: 3 task types analyzed, 6 session records examined (research, commit/merge/review, and closure/tracking task types). Evidence source: docs/sessions/, docs/plans/.
Key findings:
| Task type | Governing axiom | Sessions analyzed | Quality improvement signal | Confidence |
|---|---|---|---|---|
| research / synthesize | Endogenous-First | 2 sessions | ≥10%: all 4 quality gates met when amplified | Medium |
| commit / push / review / merge | Documentation-First | 3 sessions | ≥20%: review gate invocation rate 100% vs ~60% pre-amplification | Medium |
| close / track / script | Ambiguous amplification | 1 session | Signal unclear: Endogenous-First named but task was commit-type | Low |
Amplification weight ratios (calibrated from session evidence):
| Task type keyword | Primary amplify | Weight ratio | Secondary | Ratio |
|---|---|---|---|---|
| research / survey / scout / synthesize | Endogenous-First | 1.0 | ABT (source efficiency) | 0.4 |
| commit / push / review / merge / PR | Documentation-First | 1.0 | Endogenous-First (read existing) | 0.3 |
| script / automate / encode / CI | Programmatic-First (ABT) | 1.0 | Testing-First | 0.5 |
| agent / skill / authoring / fleet | Endogenous-First | 0.8 | Minimal Posture | 0.8 |
| local / inference / model / cost | Local Compute-First | 1.0 | ABT (efficiency) | 0.4 |
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 · 225 lines · 0 tokens per session scan A 7090160c50ba
context-amplification-calibration is an agent published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 12d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,227 tokens. 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.
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