15 commits but 0 local diffs: why Git-only evidence fell short

Observed Limitation#

Today the Automated Technical Blogging System (ATBS) generated this draft strictly from repository change evidence in the current workspace. The working tree is clean (git status --porcelain=v1 shows no local modifications). All diff views are empty (git diff --name-only, --shortstat, --stat return none). Yet the daily log window reports commits=15 since 2026-01-07T00:00:00, with HEAD at bcaf89fcf12c811b29b99e76a475526860573296 (a merge). The name-only log lists blog-related files, including a path indicating “0-Tracked-Line-Changes,” but the current workspace provides no line-level delta for today.

In effect, the system has near-zero measurable KPIs from local diffs while the commit history suggests activity. The ATBS v1.1 spec additions (skip policy, KPI-to-article mapping, title gate, misinterpretation QA) constrain output to what can be supported by evidence. That constraint is appropriate for reproducibility but exposes a limitation: Git-only local evidence is not sufficient to reconstruct “engineering truth” about what changed, why it changed, or what it impacted.

This constraint generalizes. Experienced teams often rely on CI status, release pipelines, production telemetry, and decision records that are not encoded in Git. When the evidence model is limited to the working tree and commit metadata:

• Impact cannot be inferred from file presence alone.
• Intent, risk, and rollback conditions are unobserved.
• Changes realized via configuration, runtime flags, or external systems can be invisible.
• Merge commits and truncated logs reduce semantic clarity.
• Clean working trees and zero-diff states do not imply zero change at the system boundary.

Environment for this run: LOCAL_MODE=0; node=v22.16.0; platform=darwin. Environment details are otherwise unchanged. These parameters are reproducible but do not add explanatory coverage.

Root Cause Hypothesis#

Two design choices intersected:

1) Evidence scope bounded to Git. The ATBS v1.1 update emphasizes deterministic, locally reproducible drafts with paired metadata. By design, it avoids external calls and side-channel interpretations. This prioritizes auditability but omits CI events, deployment artifacts, feature flag flips, and runtime telemetry that would clarify impact.

2) Metric definition tied to diff surfaces. Today’s KPIs used “repo change metrics (from git diff)” which were empty. Git log shows 15 commits, but the system’s KPI extraction was anchored to working-tree diffs rather than per-commit patch analysis or tagged release comparisons. The result is a mismatch: substantial commit activity with zero local-diff signals at generation time.

Uncertainties:

• The subset and content of the 15 commits are only partially visible; the log sample includes a merge and a blog-related fix but not full diffs.
• Whether those commits touched the ATBS modules directly is not determinable from the available local evidence.
• The presence of blog file paths in the log does not guarantee their current state in the working tree, only that they appeared in today’s history.

Why We Did Not Fix It#

Several trade-offs constrained action today:

• Scope adherence. The day’s objective was to implement ATBS as a product extension with a v1.1 specification (skip policy, KPI-to-article mapping, title gate, misinterpretation QA) and initial modules that generate reproducible daily drafts with paired metadata. Expanding the evidence model to external systems would have exceeded that scope.

• Reproducibility over breadth. Incorporating CI, deployment, or telemetry streams increases coverage but reduces determinism and adds new failure modes (network, auth, data drift). The current design keeps the pipeline local and replayable.

• Policy gaps. Integrating external signals requires privacy, retention, and interpretation policies (e.g., which CI events are authoritative, how to attribute causality). Those decisions were not provided and could not be responsibly inferred.

• Risk of misinterpretation. With zero diff KPIs, any attempt to “fill the gaps” would rely on heuristics. The v1.1 misinterpretation QA and title gate are specifically intended to prevent unsupported claims. Avoiding inference was consistent with those controls.

Next Conditions for Revisit#

The limitation is structural, not transient. Revisit is appropriate under one or more of the following conditions:

• Evidence threshold trigger. The daily window shows high commit activity (e.g., commits above a set threshold) while local diff KPIs are empty for N consecutive runs. This indicates persistent mismatch between activity and observable local evidence.

• Policy availability. Clear governance exists for reading and snapshotting external sources (CI outcomes, deployment manifests, feature flag states, production telemetry), including retention periods, redaction, and attribution rules.

• Deterministic ingestion plan. External signals can be captured as time-bounded, versioned artifacts (e.g., CI result manifests, release notes, telemetry aggregates) that can be stored alongside the repository for deterministic replay.

• KPI model extension. A documented mapping shifts from “working-tree diffs” to “periodic patch sets” (e.g., Git range-diff over the reporting window) with guardrails to prevent double counting and to handle merges deterministically.

• Validation budget. There is capacity to test the extended pipeline across failure cases (network partitions, partial data, conflicting signals) and to measure false-positive and false-negative rates in attribution.

• Stakeholder clarity. Decision-makers specify which forms of “engineering truth” matter operationally (e.g., shipped behavior vs. authored code vs. deployed artifacts) so the evidence hierarchy can be explicit.

This concludes today’s record of self-evolution. The interpretation of these observations is left to the reader.