⚡ CML grant-readiness dashboard

Causal Memory Layer: value, movement, and grant evidence.

A visual landing dashboard for showing why CML matters, what evidence already exists, and how the project moves toward a credible $75k–$100k grant plan.

Grant readiness
8.7 / 10
Benchmark baseline
6 / 6 matched
Target ask
$75k–$100k
Project movement

Evidence momentum

W1W2W3W4Now

Movement signal: CML now has grant evidence, benchmark baseline, Docker demo, external validation protocol, technical report outline, and a $75k–$100k execution plan.

Contributor impact

People are turning CML from artifact into community.

This board recognizes concrete project value: reproducibility, research clarity, documentation, reviewability, and trust signals. The score is a qualitative impact signal, not a competition.

🏆 @IrfanKpm Docker demo → research taxonomy → integration map 📘 @Abhishekmystic-KS plain-language audit findings glossary 🐳 @marcotannoia early Docker direction and contributor signal 🧪 @Sangha0822 API smoke-test effort under review CML community loop clear issue → useful PR → fast review → stronger evidence 🏆 @IrfanKpm Docker demo → research taxonomy → integration map 📘 @Abhishekmystic-KS plain-language audit findings glossary 🐳 @marcotannoia early Docker direction and contributor signal 🧪 @Sangha0822 API smoke-test effort under review CML community loop clear issue → useful PR → fast review → stronger evidence
@IrfanKpm
Research & reproducibility lead
Impact96
#67 Docker demo#75 patterns#78 boundaries#80 integration map

Turned CML into a more reproducible and explainable research artifact: demo path, causal-invalidity taxonomy, agentic workflow boundaries, and strategic integration hypotheses.

@Abhishekmystic-KS
Documentation clarity contributor
Impact72
#68 glossaryR1–R4 clarityreviewer onboarding

Added plain-language explanations for audit findings, making CML easier to understand for new contributors, reviewers, and non-core readers.

@marcotannoia
Early Docker direction
Impact55
#46 Docker PRruntime setupearly signal

Helped surface the importance of containerized local setup. Even where later work superseded the PR, the direction strengthened the demo/reproducibility path.

@Sangha0822
API validation contributor
Impact48
#50 smoke testsAPI surfacewaiting fixes

Proposed API smoke-test coverage for health, audit, and CTAG decode paths. The contribution is useful but still needs fixes before merge.

Maintainer note: impact scores are qualitative and may change as work is merged, validated, superseded, or expanded. The goal is recognition and contributor trust, not competition.
Value histogram

Where the project value is visible now

The strongest current value is in grant-facing clarity, core audit semantics, and reproducible demos. The next jump comes from external validation and technical reporting.

Core audit
88
Benchmark
72
Docker demo
78
Grant docs
92
External validation
45
Technical report
50
🛡️

Causal validity primitive

CML distinguishes operational success from causal legitimacy: what happened is not enough; the system must show why an action was allowed.

📊

Benchmark baseline

Current deterministic benchmark baseline: 6/6 matched cases with explicit audit findings and reproducible runner path.

🚀

$75k–$100k path

Grant plan targets 30–50 fixtures, 10–12 failure classes, external validation notes, Docker/API hardening, and a technical report.

Funding readiness

Ask ladder

The $75k–$100k range becomes credible when tied to external validation, expanded benchmarks, and a technical report.

$20k
92
$50k
84
$75k
73
$100k
61
Evidence velocity

From docs to validation

The next movement is not more words. It is reproducible evidence: more fixtures, more reports, more validators.

Fixtures target
30–50
Failure classes
10–12
Validators
2–5
Report path
Drafted
Grant roadmap

4-month execution plan

A clear delivery path for moving from early artifact to externally reproducible benchmark-backed research infrastructure.

Month 1

Taxonomy + fixture design

  • 10–12 failure classes
  • fixture metadata
  • initial 12–15 cases
Month 2

Benchmark expansion

  • 25–35 fixtures
  • positive/negative controls
  • JSON + Markdown reports
Month 3

External validation

  • 2+ validation notes
  • Docker demo hardening
  • reproduction issues tracked
Month 4

Technical report

  • 30–50 fixtures
  • final benchmark report
  • publication-ready draft
External validation target

The next proof is not louder claims. It is independent reproduction.

The strongest $75k–$100k case: 30–50 fixtures, 2–5 external validation notes, machine-readable expected findings, and a technical report that states both results and limits.

Grant ask wording

We request $75,000–$100,000 to expand CML into a benchmark-backed, externally reproducible research artifact for causal-validity checking in agentic AI workflows.