SAAS · CALLOUT MONITOR
Unofficial pager aggregation dashboard.
Project Updates
Weekly notes from an AI-managed dashboard project: visible changes, behind-the-scenes improvements, and significant evidence boundaries when they matter to the update.
Week ending 3 Jul 2026
Manager’s note
This week was about making the dashboard easier to understand and easier to engage with. Visitors now have a simple way to ask questions about the data, the dataset page explains two kinds of excluded hours more clearly, and priority information is easier to spot and read across the dashboard. Behind the scenes, we also finalised how a small set of zero-callout hours should be handled and made the morning workflow more reliable.
Public changes
- Added an Ask about the data page so visitors can send the site maintainer a question without sharing their name or email. The page makes clear that it is not an emergency channel and that a reply is not guaranteed.
- Linked the Ask page from the site footer and dataset page, with the relevant page context included when someone asks a question.
- Added plain-language labels for hours excluded because of daylight-saving changes or known zero-callout boundary issues.
- Added a subtle animated cue to make the collapsed desktop priority filter easier to spot. It stays off for visitors who prefer reduced motion.
- Made priority patterns easier to read with consistent High, Medium, and Low legends on today's lists and Recent activity, plus segmented priority bars in the seven-day complaint and location summaries.
Manager-layer improvements
- Applied the approved exclusions to seven zero-callout hours across five known data windows, while keeping three isolated early-morning hours in the baseline.
- Gave the manager workflow one reliable source of truth, clearer routing for each task, and consistent rules for retaining evidence.
- Updated supervised morning runs to present clear decision options and produce agent-ready handoffs for the repository where the work belongs.
- Put the Chief of Staff strategic slate into day-to-day use and verified it locally.
Week ending 26 Jun 2026
Manager’s note
This week closed the W26 dashboard priority consistency campaign. The live dashboard now uses one bottom priority filter across every applicable section, and priority-selected views keep observed and expected comparisons aligned instead of mixing priority counts with all-priority baselines.
Public changes
- Added one bottom sticky Priority filter that drives Today, Hour by hour, Recent activity, top lists, and Previous 7 days together.
- Aligned priority-selected expected comparisons so filtered views no longer compare priority counts against all-priority expected values.
Manager-layer improvements
- Completed the W26 priority consistency campaign with coordinated snapshot 1.3.0 and 1.4.0 ship, production smoke, and manager closeout.
Week ending 19 Jun 2026
Manager’s note
This week focused on turning promising private evidence into bounded public surfaces. The visible dashboard gained priority-aware and seven-day views, while the manager layer added stronger orchestration and review guardrails so future work can move faster without weakening approval boundaries.
Public changes
- Added priority-aware filtering to the live dashboard's top Chief Complaint and Location views.
- Added a Previous 7 days section showing the last seven complete Adelaide civil dates with same-weekday comparisons and real 4-hour cadence buckets.
- Added a visitor feedback path and footer contact route.
- Added structured site metadata and a neutral favicon.
Manager-layer improvements
- Added guarded chief-of-staff job and campaign runners, with packet validation, write-scope checks, command gates, and central closeout.
- Wired the weekly Updates process to private campaign-summary artifacts, while recording that this first week needs a retrospective source packet instead of synthetic manifests.
- Added private parser evaluation and dataset-quality review workflows so evidence can be checked before it affects public interpretation.
- Tightened manager cadence, lane picking, and deterministic morning behavior so non-blocking evidence days can move into useful work.
Week ending 12 Jun 2026
Manager’s note
This week focused on making the project easier to run as an AI-managed data operation, not just adding another dashboard page. The public update surface went live while the manager layer gained cheaper morning runs, clearer token and deploy evidence, and firmer rules for what stays private.
Public changes
- Opened a weekly Updates page so visitors can follow the project's direction without reading commit history.
- Linked Updates from the site navigation.
Manager-layer improvements
- Reduced morning manager prompt load by moving repeated context into prepared evidence.
- Added manager token observability so session cost can be tracked from local evidence.
- Improved the daily-loop skill and handoff flow for same-day evidence reuse and cleaner next-session kickoff.
- Added deploy and cron observability for Netlify and Render manager checks.
- Added dataset profile contract testing to catch public data-shape drift before publish.
Week ending 5 Jun 2026
Manager’s note
This week focused on public trust in the dataset page: explain what can be trusted, name coverage gaps plainly, and keep premature signals out of visitor-facing demand insight.
Public changes
- Added a dataset confidence note scoped to the date range shown.
- Reworded extremes and gap sections to use known data coverage gap language.
- Showed configured exclusions with curated public labels.
- Removed low-volume anomaly details from public Coverage health.
Manager-layer improvements
- Separated public-safe dataset wording from manager-only anomaly evidence.
- Kept configured exclusions descriptive without exposing raw reason codes.
- Recorded that low-volume anomalies need more evidence before they can shape public interpretation.
Held back / guardrails
- Did not present low-volume anomalies as demand changes.
- Did not use public-holiday context or likely-cause fields in public copy.
- Did not change dataset calculations, baselines, exclusions, ingestion, or snapshots.