Start your search now across code repositories, users, issues, and pull requests with a single, fast tool. It handles multiple requests in parallel, surfaces pushed commits and related issues in context, and delivers precise results in seconds. Configure required filters to narrow results and stay focused on what matters.
The product runs in a container with UTF-8 encoding and supports common search operators, so you can craft nuanced queries without extra setup. Efficient indexing keeps the most relevant items on top, even as new data arrives from accounts, forks, and collaborators. The documentation clarifies terminology and data schemas to speed onboarding.
Documentation and guided workflows explain how to tailor searches, how to interpret results, and how to export data safely. The platform is supported on teams of any size and integrates with your existing accounts and IAM policies.
Export results as CSV using csv_datacsv_data fields and leverage my_csv_glossary to map terms to columns for easy integration. For executing searches, the dashboard or API returns results in seconds, and you can push updates to your analytics pipeline with a single request. The system keeps accounts and permissions in sync and offers robust auditing for every request.
Identify core user personas and their day-to-day search tasks
Define three core groups: engineers, testers, and product owners. For each, publish five ready-to-use search templates and tag them with a short label for quick reuse.
Engineers routinely locate patches by author, identify where changes touched the codebase, and filter by module, file type, or directory. Build templates that cover common paths, recent activity, and language-specific files to speed the lookup.
Testers focus on failing runs, error traces, and regression indicators. Filter results by service, environment, and recent fixes to confirm stability; track recurring error patterns and cross-reference with recent patches.
Product owners map work to outcomes: link issues to features, monitor release readiness, and assess progress via status and timeline filters. Use queries that group by milestone and by affected component to prepare ready-to-review dashboards.
Cross-cutting guidance: create a centralized glossary and keep it up to date so multilingual teams interpret terms consistently. Provide a lightweight mapping that translates common terms into several languages and flows naturally in the UI.
Metadata shown with each result includes author, date, module, and path, plus a concise outcome label. This supports triage and reduces follow-up queries.
Tips for adoption: offer a role-based UI, provide five starter collections per persona, and allow saving as labeled collections. Ensure filters are intuitive and load results within seconds.
Operational considerations: periodically review templates for relevance, remove outdated ones, and add new templates as the codebase grows. Track usage metrics to understand which templates help teams resolve issues faster.
Show live workflows: saving, organizing, and reusing searches for repos, users, issues, and PRs
Save each targeted search as a live workflow and pin it to your workspace; this represents a repeatable path you can run on demand for repos, users, issues, and PRs.
Name each workflow clearly and set a consistent format for searches, including filters, columns, and a csv_data export option so teammates can import results into their pipelines; you may wish to include a short description, and you can filter out invalid results.
On macos, install the included plugin such as deepldeeplexception, then use actions for constructing replacement_entries and override default scopes to fit your accounts.
Expose results to diverse audiences: japanese labels, british teams, and scientific readers, and attach an article or papers that explain the data fields; keep an updated_glossary to reflect changes and preserve quality.
Later, reuse searches across repos and PRs by saving them as live workflows, enabling proton-powered collaboration and making results available to your team.
Provide a practical query syntax guide with ready-to-use examples
Start with a concise query that narrows scope by repo, author, and date. Example: repo:owner/repo is:pull_request is:open author:alice created:>=2024-01-01 version:1.2 cross-platform sort:created-desc. This keeps results readable, supports cross-platform workflows, and lets you interact with items quickly. Customize with plus and optional constraints, and override default sorts when you need a targeted view. For multilingual teams, translates:english helps unify results across locales. If your codebase uses aspnet styles, include path:src/aspnet and label:styles to refine results. You can read the results and act on them directly from the list.
Qualifiers and constraints are described here: required fields like doc_id or version must be specified for targeted lookups; optional qualifiers extend results; override applies to the current session; chatcompletioncreaterequest signals a request node; checks enforces validations; specified marks explicit intent; from and date filter by origin and time; modelschatgpt3_5turbo sets AI context; translates:english standardizes language.
Syntax overview
Qualifiers are space-separated with a name and value. Use created:, updated:, and date: ranges, plus from: to filter by author or source. Use is:, repo:, user:, author:, assignee:, label:, milestone:, and path to tighten results. Values containing spaces go in quotes. Use optional constraints to refine, and mark required fields when targeting a doc or artifact (doc_id, version). If a field is unspecified, defaults apply, but you can override them with explicit qualifiers.
Ready-to-use examples
Open PRs in a repo by a specific user since a date: repo:owner/repo is:pull_request is:open author:alice created:>=2024-01-01 version:1.2 sort:created-desc
Issues assigned to a user with a label: is:issue assignee:bob label:bug is:open created:>=2024-05-01
PRs targeting main updated recently: repo:owner/repo is:pull_request base:main sort:updated-desc created:>=2024-09-01
Docs search with doc_id and AI model context: doc_id:12345 model:modelschatgpt3_5turbo chatcompletioncreaterequest translates:english from:system specified:true checks:true override:false plus
Build compelling proof points: time savings, onboarding improvements, and collaboration gains
Start by targeting a 30% reduction in PR cycle time within 60 days using a real-time dashboard spanning all repositories and accounts.
Économies de temps
- Real-time prioritization eliminates manual triage, cutting average triage time by 40% and accelerating issue-to-PR flow when all activity appears in a single view.
- Automated metrics track time to respond, time to merge, and test durations, enabling targeted process tweaks without overhauling your stack.
- Containerized dashboards run with a single container, ensuring full visibility across teams and environments with minimal setup.
- mock-server-session accelerates testing by providing offline mocks, reducing environment provisioning time by up to 60%.
- Logging aggregates results in real-time, so teams see progress without manual reporting and can react within the same day.
- translate_document_from_filepath and deepl_client enable multilingual updates to runbooks and guides, expanding coverage without delaying ship dates.
Onboarding improvements
- New contributors reach first PR in 2 days vs 5 days with guided onboarding tasks and a unified markdown view of starter issues.
- Multilingual onboarding documents are translated automatically with deepl_client, targeting target_langde to support German-speaking contributors.
- translate_document_from_filepath automates localization of critical docs, so new hires access accurate guidance in their language.
- Accounts and client templates unlock a clean, dual-path setup: personal sandbox plus organization workspace, reducing confusion during first hours.
- Manually actionable checklists become automated playbooks, lowering questions at kickoff and enabling teams to start coding sooner.
- Logging captures onboarding steps and outcomes, providing visible results for managers and mentors.
Collaboration gains
- Dual collaboration modes let teammates work in parallel via real-time co-editing, while a separate client session handles reviews and approvals.
- Multilingual collaboration improves clarity across distributed teams; texts in multiple languages stay aligned through translation pipelines and target_langde support.
- mock-server-session and container-based environments create safe, shared spaces for experimentation, reducing cross-team conflicts.
- A robust value loop ties feedback to results: you can measure behaviour changes in review times, merge speeds, and issue reopen rates.
- Additionally, the centralized logging and results tracking give teams a full view of collaboration health across accounts and projects.
- Plus, a streamlined SAPIKey (sapikey) workflow secures client access while enabling real-time syncing and translate workflows without friction.
- You can start small with a markdown-based dashboard, then scale to a full multilingual view that supports translate_document_from_filepath and other automation gates.
Plan distribution assets and onboarding flows for trial users
Issue a single, versioned trial bundle from your server with a guided onboarding flow and a lightweight readme. The bundle stays free during the trial and uses UTF-8 encoding to support multiple locales. Provide a short expiry on access tokens to prevent stale installs and unexpected charges.
Package distribution assets as a compact, self-contained folder: csv_datacsv_data sample dataset to seed repos; a mock-server-session script for local testing; a doc_id generator to correlate events; translator strings for UI localization; a pair of quick-start guides for Chrome and Flutter; and a small rust-based validation agent to verify requests before exposure to the app. This setup minimizes friction and accelerates onboarding across desktop and mobile users.
The onboarding experience should guide users through three parallel paths: Chrome extension onboarding, Flutter mobile onboarding, and a REST/API client path. Each path includes a concise, action-oriented flow, toggled field visibility depending on eligibility, and a translation layer. Pair the steps with push updates and ensure responses are captured in the printentries_responsedictionaries0 structure for analytics. Include a toggle that disables non-essential features in trial mode to prevent feature leakage.
Define clear success metrics and update cadence. Target a time-to-first-action under 60 seconds for most users, a 65-70% completion rate, and mobile onboarding adoption above 40%. Encode and expose response data via a lightweight metrics endpoint. Use the doc_id system to correlate events across sessions and store key events in responses for debugging. Track channels (web chrome, iOS/Android Flutter) and keep a compact encoding to simplify cross-path reporting.
Operational controls and reviews. Use the server to push updates without breaking existing trial configurations; verify encoding integrity across locales; disable non-essential features in trial mode to prevent feature leakage; and ensure a simple rollback path for failed updates. Track changes over years of usage and keep changelog entries accessible to QA and support teams. Maintain a compact field map to align UI prompts with backend responses and minimize API surface exposure.
| Asset | Delivery method | Purpose | KPI | Notes |
|---|---|---|---|---|
| Distribution bundle (server) | Versioned ZIP URL with access token | Trial onboarding bundle | Time-to-first-action < 60s; completion rate > 65% | Free tier; expires after defined period |
| csv_datacsv_data sample | Included CSV; loaded via API | Seed sample repositories | Preview success rate > 75% | Used by mock-server-session during tests |
| mock-server-session script | GitHub repo or internal registry | End-to-end testing | Responses latency < 200ms | Simulates API endpoints for onboarding demos |
| translator + localization | JSON bundles per locale | UI clarity across locales | Localization coverage > 90% | Supports chrome and flutter paths |
| doc_id telemetry | Embedded in bundle; optional remote | Event correlation | Errors < 1% | Links onboarding steps to analytics |
| printentries_responsedictionaries0 | In-memory during onboarding | UI responses mapping | Responses captured for debugging | First batch of responses used for validation |
