g-gremlin 0.1.26

Little AI gremlin in your sheet.

g-gremlin — the little AI gremlin in your sheet

Local-shadow CLI for Google Sheets that pulls to CSV, diffs, and pushes back with safety rails (concurrency token, formula protection, previews).

Setup

• Python 3.11+
• From repo root: python -m pip install --upgrade pip then python -m pip install -e .
• If you have an older g-gremlin in user/site-packages, remove it first. A stale non-editable install can shadow the repo checkout in ad hoc Python runs.
• Obtain a Google OAuth client (Desktop app) from Google Cloud Console.
  • Set G_GREMLIN_CREDENTIALS=/path/to/credentials.json or place it at ~/.g_gremlin/credentials.json.
• Tokens live at ~/.g_gremlin/token.json; delete to re-auth.

MCP

• Install the MCP runtime with package extras:

  python -m pip install "g-gremlin[mcp]"
  

  or with pipx:

  pipx install "g-gremlin[mcp]"
  

• Canonical CLI entrypoint:

  g-gremlin mcp serve --provider sfdc
  

• Wrapper-friendly launcher:

  g-gremlin-mcp --provider sfdc
  

• Providers currently exposed through the MCP runtime:
  • sfdc
  • dynamics
  • apollo
  • outreach
  • zoominfo
• Auth bootstrap remains CLI-first. Configure credentials before attaching a host:
  • Salesforce: g-gremlin sfdc connect --org-alias <alias>
  • Dynamics: g-gremlin auth set dynamics
  • Apollo: g-gremlin auth set apollo
  • Outreach: g-gremlin outreach oauth connect
  • ZoomInfo: g-gremlin zoominfo oauth connect
• First smoke tests after install:
  • g-gremlin-mcp --help
  • Connect a host or inspector and call sfdc.doctor, dynamics.doctor, or zoominfo.doctor
• Starter MCP prompts now ship in the server for the first-run workflows:
  • crm-doctor on sfdc and dynamics
  • sfdc-snapshot on sfdc
• Host-specific setup examples live in docs/runbooks/mcp_host_setup.md.

Usage

• Pull a range to CSV:

  g-gremlin pull SPREADSHEET_ID --range "Leads!A1:Z" --output leads.csv
  

• Diff two CSVs:

  g-gremlin diff --original leads.csv --modified leads_edited.csv --key-col Id --limit 10
  

  • Summary + preview; writes .g_gremlin/diff.json.
• Push changes back (ETag/concurrency guarded, formula-aware):

  g-gremlin push --dry-run   # preview updates
  g-gremlin push             # apply updates
  

  • Uses .g_gremlin/state.json and .g_gremlin/diff.json.
  • Requires a concurrency token from the last pull; if missing, re-run pull.
  • Skips cells that contain formulas (warns) and aborts if the remote version changed unless --force is provided.
• Validate a CSV against rules:

  g-gremlin validate --csv account_dim.csv --rules rules/account_dim.yaml --output .g_gremlin/validate_result.json
  # or run a formula pre-flight (no rules) with allowed sheet refs:
  g-gremlin validate --csv model.csv --refs "FY26_Assumptions,FY27_Assumptions"
  

• Inspect (profile) a sheet without modifying it:

  g-gremlin inspect                # uses state.json from last pull
  g-gremlin inspect -s SPREADSHEET_ID -r "Leads!A1:E200" -o .g_gremlin/profile.json
  

  • Reads values and formulas, infers column types/stats, lists formula cells.
  • Captures named ranges and a basic role per column (dimension/measure/derived/unknown) to help AI tools understand inputs vs metrics vs derived outputs.
  • Writes .g_gremlin/profile.json; running inspect before heavy workflows helps avoid overwriting formulas during push.
  • Semantic inspect adds semantic_type (e.g., sfdc_account_id, date_excel_serial), optional validation, tab classification, and detected_sfdc_patterns to the JSON profile.
  • Use --structure to capture formula dependency graphs (drivers, OFFSET lags, IFERROR wrappers, cross-sheet refs).
  • Use --lint to scan formulas for common issues; combine with --fix to auto-quote bad sheet references.
• Repair inherited spreadsheets (the "broken model" rescue flow):

  g-gremlin repair analyze -s SPREADSHEET_ID -r "Model!A1:Z100" -o repair_plan.json
  g-gremlin repair fix --plan repair_plan.json --auto -s SPREADSHEET_ID
  g-gremlin repair fix --plan repair_plan.json -s SPREADSHEET_ID   # interactive for remaining items
  

  • Use repair stub-sheets to create placeholders for missing tabs; repair patterns for anomaly-only scans; repair diff to compare to a baseline tab/file.
  • repair diff accepts --baseline (CSV file), --baseline-tab, or --baseline-sheet and writes .g_gremlin/repair_diff.json.
• Send in the gremlin (hero command):

  g-gremlin rescue SPREADSHEET_ID \
    --band "J:M=FY26_Assumptions" \
    --band "N:Q=FY27_Assumptions" \
    --receipt
  

  • Scans all tabs, fixes everything it safely can, prompts only when needed (e.g., missing sheet remap vs stub), writes a JSON report to .g_gremlin/rescue_report.json, and a receipt to .g_gremlin/rescues/ when requested. Flags: --dry-run, --auto, --output FILE, --receipt, --backup/--no-backup (placeholder), --throttle/--no-throttle (pacing + quota backoff; default on).
• Style a range (headers/stripes/fonts):

  g-gremlin style -s SPREADSHEET_ID -r "Tab!A1:Q200" --header-fill "#1f4e79" --stripe --font-size 11
  

  • Flags: --header-rows, --header-bold/--no-header-bold, --header-fill, --header-font-color, --stripe/--no-stripe, --stripe-color, --font-size, --font-color.
• Write a CSV directly to a tab (creates it if missing):

  g-gremlin write SPREADSHEET_ID --tab "Cleaned" --csv cleaned.csv --mode overwrite
  g-gremlin write SPREADSHEET_ID --tab "Cleaned" --csv delta.csv --mode append
  # with backup copy before writing:
  g-gremlin write SPREADSHEET_ID --tab "Master_Enriched" --csv master_final.csv --mode overwrite --backup
  

• Copy a tab safely (preserves cross-sheet references):

  g-gremlin copy-tab SPREADSHEET_ID --source "MH 2026" --dest "Orion_FY27_Assumptions" --overwrite
  

  • Merge multiple CSVs by key with optional source flags:

    g-gremlin merge --sources cw_opps.csv,commure_opps.csv --key "Account ID" --output merged.csv --source-flag-col Source
    

  - Fuzzy-match names between two files:
    ```bash
    g-gremlin fuzzy-match --source master_list.csv --source-col "Account Name" --target account_dim.csv --target-col AccountName --output matched.csv --threshold 0.8
  

• Quick safety + doctor checks:

  g-gremlin doctor SHEET_ID --live --sfdc --format json --output doctor.json
  g-gremlin safety
  

  • Machine output standard: --format json (alias --json) + --output PATH (use - for stdout). --json-summary remains a shortcut on mutating commands.
• Connect Apollo OAuth for FoundryMatch enrichment:

  g-gremlin apollo setup --show-redirect-urls
  g-gremlin apollo auth --workspace-id YOUR_WORKSPACE_ID
  g-gremlin apollo doctor --dev
  

  • Register the redirect URL printed by g-gremlin apollo setup in Apollo (single callback for Sheets + CLI).
  • Full setup guide: docs/APOLLO_OAUTH_SETUP.md.
• Audit Zendesk and Salesforce identity drift with the starter workflow:

  g-gremlin zendesk drift init --sf-csv ./salesforce_accounts.csv
  g-gremlin zendesk drift audit --config ./gremlin.zendesk_drift.yaml
  g-gremlin zendesk drift trace --config ./gremlin.zendesk_drift.yaml --sf-account-id 001ACME
  g-gremlin zendesk drift apply --plan ./artifacts/zendesk_drift/<run_id>/fix_plan.json
  

  • Live apply is opt-in and requires both --apply and --confirm-plan-hash.
  • Canonical workflow doc: docs/runbooks/zendesk_drift_workflow.md.

Recipes (agent-friendly)

• Deploy a spreadsheet model: g-gremlin diff ... (optional) → g-gremlin lint ... → g-gremlin sync SHEET_ID --config g_gremlin.yaml (dry-run preview) → g-gremlin sync ... --apply (backed up; plan hash + run ID emitted).
• Resolve accounts to SFDC + writeback: g-gremlin pull ... --range "Accounts!A:Z" --output accounts.csv → match domains with g-gremlin fg search/fg lookup or g-gremlin fuzzy-match → stage updates in CSV → g-gremlin sfdc preview-push --csv updates.csv --object Account --id-column Id --fields "Type,Industry" --output preview → g-gremlin push --dry-run → g-gremlin push.
• Build contacts from an account universe: export with g-gremlin pull ... --range "Contacts!A:Z" → enrich with g-gremlin enrich --csv contacts.csv --company-col Company --output enriched.csv → dedupe/merge via g-gremlin fuzzy-match or merge → link IDs in the sheet with g-gremlin write/sync (prefer dry-run first).
• Notify a webhook on completion (piped from another command):

  g-gremlin sync SHEET_ID --config sync.yaml --apply --json-summary \
    | g-gremlin notify webhook https://hooks.slack.com/... --apply
  

• Sequence contacts (Instantly, Smartlead, Apollo):

  g-gremlin sequencer doctor --provider apollo
  g-gremlin sequencer campaigns list --provider instantly --format json
  g-gremlin sequencer push --provider smartlead --csv leads.csv --campaign-id XYZ --apply
  

  • Credentials: set G_GREMLIN_INSTANTLY_API_KEY, G_GREMLIN_SMARTLEAD_API_KEY, or G_GREMLIN_APOLLO_API_KEY (or use g-gremlin auth set ...).

Command map (everything in the CLI)

• pull / write / push — core read/write with concurrency + formula safety.
• diff / merge / fuzzy-match / transform — local CSV utilities.
• inspect / inspect-formulas / find-refs / trace / check-bands / generate-lag — analysis/lineage helpers.
• repair / rescue / copy-tab / style — sheet fixing and formatting.
• sync / names / ranges / formula — config-driven writes, named range, and formula helpers.
• lint / validate / schema-validate — linting and schema validation.
• enrich / fullenrich / dedup / apify / hubspot / sfdc / zendesk / fg / outreach / gdocs / gslides — enrichment, dedup, and integrations (Apify, HubSpot, Salesforce, Zendesk, FoundryGraph, Outreach, Google Docs, Google Slides).
• apollo — Apollo OAuth connect/check/disconnect for FoundryMatch enrichment (server-held tokens).
• recipe / chain — prebuilt flows and chained pull→enrich→transform→write (with optional sink).
• query — DuckDB-backed read-only SQL over CSV/Parquet.
• sink — land CSV data to BigQuery, S3, GCS, Snowflake, or Redshift.
• snapshot — create/list/diff/restore spreadsheet snapshots with rollback support.
• notify — job-level notifications to webhooks (Slack/Discord/custom).
• sequencer — push contacts to Instantly, Smartlead, or Apollo sequences.
• provenance — sidecar cleanup; stats — gremlin achievements.
• autopilot — localhost web UI + CLI-runnable plays (workflow templates).
• docs / help — built-in docs and JSON introspection.

Autopilot Plays

Pre-built workflow templates that run without AI assistance. They extract data and metadata from connected systems into structured artifacts for documentation and analysis.

Quick Start

# List available plays (shows credential status)
g-gremlin autopilot play list

# Validate a play definition
g-gremlin autopilot play validate document_cpq

# Run a play (dry-run preview)
g-gremlin autopilot play run test_echo --dry-run

# Run a play with parameters
g-gremlin autopilot play run document_cpq -p output_format=markdown

# Specify output directory
g-gremlin autopilot play run document_cpq --output-dir ./my_output

Available CRM Documentation Plays

Play	Description	Credentials
document_cpq	Document CPQ config (products, pricing, quotes)	salesforce
document_lead_routing	Document lead assignment and territories	salesforce
document_case_routing	Document case routing and entitlements	salesforce
document_renewals	Document renewal process and contracts	salesforce
document_revenue_process	Document opportunity stages and forecasting	salesforce
test_echo	Smoke test play (no external dependencies)	none

Output Structure

Each play run creates an artifacts directory:

artifacts/<play_name>/<timestamp>/
  metadata_inventory.md     # Summary of extracted data
  final_doc.md              # Documentation skeleton
  risks_and_edge_cases.md   # Automated risk flags
  run_summary.json          # Execution details + step results
  logs/                     # Per-step execution logs
  metadata/                 # Retrieved SF metadata (flows, validations)
  *.csv                     # Extracted data files

Operator Prompts

Each CRM play has a matching .prompt.md file in config/plays/ for AI-assisted synthesis:

1. Run the play to extract data
2. Use the operator prompt with an AI assistant to synthesize artifacts into client-ready documentation

Documentation

• PLAYBOOKS.md — Full user guide
• PLAY_AUTHORING.md — Create custom plays
• AUTOPILOT_SCOUTS.md — Scout catalog and configuration

Gremlin Triage (Sheets add-on)

One-click answer to “What should I do with this sheet?”

• Endpoint: POST /api/v2/gremlin/triage (headers: X-Sheets-Token), body: { spreadsheet_id, sheet_name?, range? } (defaults to active sheet, A1:Z2000).

• Returns: deterministic summary (row/col counts, headers, SFDC ID detection, B2C/duplicate %, formula density), suggested_actions (2-4 routed flows), optional ai_summary for Pro+ tiers.

• Client entry points: Sheets add-on sidebar button “🧭 What should I do with this?” and menu: FoundryMatch → Model Intelligence → 🧭 What should I do?

• Actions route to existing flows (scan/fix/explain model, dedupe, match to accounts, SFDC enrich placeholders). Free tiers get deterministic summary; Pro/Scale/Unleashed add AI natural-language summary (Gemini).

• Model building helpers:

  # Pre-flight validate a CSV and allowed sheet refs
  g-gremlin validate --csv model.csv --refs "FY26_Assumptions,FY27_Assumptions"
  
  # Check column bands reference expected sheets
  g-gremlin check-bands --csv model.csv --band "J:M=FY26_Assumptions" --band "N:Q=FY27_Assumptions"
  
  # Generate lagged OFFSET formulas across a row
  g-gremlin generate-lag --source "E5:Q5" --lag 2 --output lag_row.csv
  # Copy a tab safely without breaking cross-sheet references
  g-gremlin copy-tab SPREADSHEET_ID --source "Template" --dest "Target" --overwrite
  

• Salesforce helpers:

  g-gremlin sfdc connect --org-alias canopy
  g-gremlin sfdc audit --csv account_dim.csv --id-column AccountId --object Account --report .g_gremlin/sfdc_audit.json
  g-gremlin sfdc enrich --csv account_dim.csv --id-column AccountId --object Account --fields Type,Industry --output account_enriched.csv
  # Aliasing fields:
  g-gremlin sfdc enrich --csv account_dim.csv --id-column AccountId --object Account --fields "CS_Scorecard_GPA__c AS 'CS Scorecard GPA'" --output account_enriched.csv
  # Preview SFDC changes from a CSV (does not push):
  g-gremlin sfdc preview-push --csv master_final.csv --object Account --id-column AccountId --fields Type,Industry --output sfdc_preview
  

  • sfdc audit checks ID format, prefix, duplicates, and SFDC existence; default report path is .g_gremlin/sfdc_audit.json.
  • sfdc preview-push only compares CSV vs SFDC and writes <output>.json and <output>.md; it never writes to SFDC.
  • Zendesk:

    g-gremlin zendesk connect --subdomain your_subdomain --email [e-mail] --api-token ****
    

  • Recipe: build a simple Account Dim from opp exports:

    g-gremlin recipe build-account-dim --opp-sources cw_opps.csv,commure_opps.csv --key-column "Account ID" --name-column "Account Name" --output account_dim.csv
    # with optional master list attach
    g-gremlin recipe build-account-dim --opp-sources cw_opps.csv,commure_opps.csv --key-column "Account ID" --name-column "Account Name" --master-list master.csv --master-name-col "Account Name" --output account_dim.csv
    # optional: specify stage/close/amount columns to compute Has_ClosedWon, ARR_Estimate, latest close/end dates
    g-gremlin recipe build-account-dim --opp-sources cw.csv,commure.csv --key-column "Account ID" --name-column "Account Name" --stage-column "StageName" --close-date-column "CloseDate" --amount-column "Amount" --output account_dim.csv
    

  • Recipe: enrich-from-sfdc (recipe wrapper for sfdc enrich):

    g-gremlin recipe enrich-from-sfdc \
      --csv account_dim.csv \
      --id-column AccountId \
      --object Account \
      --fields Type,Industry,BillingCity \
      --output account_enriched.csv
    

  • Recipe: resolve-unmatched (surface rows missing IDs with SOQL hints):

    g-gremlin recipe resolve-unmatched \
      --csv account_dim.csv \
      --id-column AccountId \
      --name-column "Original_Master_Name" \
      --output unmatched.csv
    

  • Recipe: detect open renewals on accounts:

    g-gremlin recipe detect-open-renewals \
      --csv account_dim.csv \
      --id-column AccountId \
      --renewal-col "Open Renewal?" \
      --renewal-id-col "Open Renewal ID" \
      --output account_dim_with_renewals.csv
    

  • Recipe: attach products from OpportunityLineItems per account:

    g-gremlin recipe attach-products \
      --csv account_dim_with_renewals.csv \
      --id-column AccountId \
      --products-column "Direct Products" \
      --stage "7 - Closed Won" \
      --output master_enriched.csv
    

  • Recipe: Zendesk user stats by email:

    g-gremlin recipe zendesk-user-stats \
      --csv master_enriched.csv \
      --email-column "Primary Contact Email" \
      --tickets-count-col "ZD Ticket Count" \
      --open-tickets-col "ZD Open Tickets" \
      --last-ticket-col "ZD Last Ticket At" \
      --output master_with_zd.csv
    

  • Recipe: Zendesk org stats by org URL/ID:

    g-gremlin recipe zendesk-org-stats \
      --csv master_enriched.csv \
      --org-column "Zendesk_URL" \
      --total-tickets-col "ZD_Total_Tickets" \
      --open-tickets-col "ZD_Open_Tickets" \
      --last-ticket-col "ZD_Last_Ticket_At" \
      --org-created-col "ZD_Created_At" \
      --output master_with_org_stats.csv
    

  • Transform a CSV (rename/add/calculated columns):

    g-gremlin transform --input data.csv --output data_out.csv --rename Old=New --add-column CSM_Assigned --calc "Days_To_Renewal=Latest_End_Date-TODAY"
    

  • Chain pull → enrich → transforms → write → sink:

    </code></pre>
    </li>
    </ul>
    <p>g-gremlin chain --spreadsheet-id SPREADSHEET_ID --pull-range "Sheet!A1:Z" <br />
    --enrich-object Account --enrich-fields "Type,Industry" --enrich-id-column AccountId <br />
    --calc "Days_To_Renewal=Latest_End_Date-45997" --add-column "CSM_Assigned" <br />
    --write-tab "Output_Tab"</p>
    <h1><a href="#user-content-chain-with-sink-to-bigquery" aria-hidden="true" class="anchor" id="user-content-chain-with-sink-to-bigquery"></a>Chain with sink to BigQuery</h1>
    <p>g-gremlin chain --spreadsheet-id SPREADSHEET_ID --pull-range "Data!A1:Z" <br />
    --enrich-object Account --enrich-fields "Type,Industry" <br />
    --sink bq --sink-project myproj --sink-dataset revops --sink-table enriched</p>
    <pre><code>- Chains pull → optional SFDC enrich → transforms → optional write → optional sink; default output lands at `.g_gremlin/chain/chain_output.csv`.
    - Manifest example at `.g_gremlin/state.json`:
      ```json
      {
        "spreadsheet_id": "...",
        "range": "Leads!A1:Z",
        "output_file": "leads.csv",
        "concurrency_token": "...",
        "pulled_at": "2025-01-01T12:34:56Z"
      }
    

    Example flow

    • Pull, merge two sources, fuzzy-match account names to a dimension, then write back:

      g-gremlin pull SPREADSHEET_ID --range "Opps!A1:Z" --output opps.csv
      g-gremlin merge --sources opps.csv,commure_opps.csv --key "Account ID" --output merged.csv --source-flag-col Source
      g-gremlin fuzzy-match --source merged.csv --source-col "Account Name" --target account_dim.csv --target-col AccountName --output matched.csv --threshold 0.82
      g-gremlin write SPREADSHEET_ID --tab "Matched" --csv matched.csv --mode overwrite
      

      • Extend with SFDC enrich:

      g-gremlin recipe build-account-dim --opp-sources opps.csv,commure_opps.csv --key-column "Account ID" --name-column "Account Name" --output account_dim.csv
      g-gremlin sfdc enrich --csv account_dim.csv --id-column "Account ID" --object Account --fields Type,Industry,BillingCity --output account_dim_enriched.csv
      g-gremlin write SPREADSHEET_ID --tab "Master_Enriched" --csv account_dim_enriched.csv --mode overwrite
      

  Backup & Rollback

  All destructive commands support automatic backup snapshots with restore-on-error:

  # Backup is ON by default for: write, push, repair fix, rescue, sync, chain, copy-tab, style
  g-gremlin write SPREADSHEET_ID --tab "Data" --csv data.csv            # Creates pre-write snapshot
  g-gremlin write SPREADSHEET_ID --tab "Data" --csv data.csv --no-backup  # Skip backup
  
  # Auto-rollback for CI/agents (restores on any error)
  g-gremlin push SPREADSHEET_ID --auto-rollback
  
  # Manual snapshot management
  g-gremlin snapshot create SPREADSHEET_ID --name "before-refactor" --tabs "Sheet1,Sheet2"
  g-gremlin snapshot list SPREADSHEET_ID --json
  g-gremlin snapshot diff SPREADSHEET_ID --name "before-refactor"
  g-gremlin snapshot restore SPREADSHEET_ID --name "before-refactor"
  g-gremlin snapshot restore SPREADSHEET_ID --name "before-refactor" --force  # Override safety checks
  

  Safety checks on restore:

  • ETag mismatch: Blocked if spreadsheet modified since snapshot
  • Shape drift: Blocked if rows/columns changed
  • Use --force to override (data may be lost)

  Data Sink (g-gremlin sink)

  Land CSV data to external systems:

  # BigQuery
  g-gremlin sink bq --csv accounts.csv --project myproj --dataset revops --table accounts --mode replace
  
  # S3 / GCS
  g-gremlin sink s3 --csv data.csv --bucket my-bucket --prefix exports/2025/ --compress
  g-gremlin sink gcs --csv data.csv --bucket my-bucket --prefix exports/2025/ --compress
  
  # Snowflake (via S3/GCS staging)
  g-gremlin sink snowflake --csv accounts.csv \
    --stage-bucket my-staging --database ANALYTICS --schema REVOPS --table ACCOUNTS
  
  # Redshift (via S3 staging)
  g-gremlin sink redshift --csv accounts.csv \
    --stage-bucket my-staging --host cluster.redshift.amazonaws.com \
    --database analytics --schema revops --table accounts \
    --iam-role arn:aws:iam::123456789:role/RedshiftCopyRole
  
  # Cleanup old staging files
  g-gremlin sink cleanup --older-than 7 --delete-from-cloud
  

  Optional dependencies:

  pip install g-gremlin[sink-bq]        # BigQuery
  pip install g-gremlin[sink-s3]        # S3 (boto3)
  pip install g-gremlin[sink-gcs]       # GCS
  pip install g-gremlin[sink-snowflake] # Snowflake
  pip install g-gremlin[sink-redshift]  # Redshift (psycopg2)
  pip install g-gremlin[sink-all]       # All sinks
  

  Notes

  • Dependencies: click, google-auth, google-auth-oauthlib, google-api-python-client, requests, pyyaml.

  Close the GTM Loop (Common Room → HeyReach → Docs)

  • New integrations: Common Room (CSV ingest now; webhooks later), HeyReach activation, docs sinks (Notion + Outline + Confluence). They are independent entry points; use the ones you need.
  • Safety: All mutation commands are dry-run by default; add --apply to execute. Defaults are conservative (HeyReach 10/batch, 500ms delay, 100/day; Notion 3 req/sec built-in; Outline honors Retry-After on 429s).
  • Notion updates replace the existing page body to keep re-publish idempotent. Large pages can update slowly because Notion requires per-block deletes, and if a replace fails mid-flight the next publish will repair the page body.
  • Quick start (pick any provider):

    g-gremlin auth set commonroom --key webhook_secret
    g-gremlin commonroom doctor
    g-gremlin commonroom import --source signals.csv --output enriched.csv --min-intent-score 0.6 --apply
    
    g-gremlin auth set heyreach --key api_key
    g-gremlin heyreach doctor
    g-gremlin heyreach enroll --csv enriched.csv --campaign-id ABC123 --apply
    
    g-gremlin auth set notion --key token
    g-gremlin docs doctor --provider notion
    g-gremlin docs publish-batch --csv enriched.csv --provider notion --database-id XYZ789 --template src/g_gremlin/templates/intent-brief.md.j2 --external-id-column signal_id --apply --profile prod
    
    g-gremlin auth set outline --key api_token
    g-gremlin auth set outline --key api_base --value https://wiki.example.com/api
    g-gremlin docs doctor --provider outline
    g-gremlin docs publish-batch --csv enriched.csv --provider outline --collection-id COLLECTION_ID --template src/g_gremlin/templates/intent-brief.md.j2 --external-id-column signal_id --apply --profile prod
    
    g-gremlin auth set confluence --key api_base --value https://acme.atlassian.net
    g-gremlin auth set confluence --key email --value [e-mail]
    g-gremlin auth set confluence --key api_token --value $CONFLUENCE_TOKEN
    g-gremlin docs doctor --provider confluence
    g-gremlin docs publish --provider confluence --markdown-file plan.md --space-key SPACE --apply
    

  • Outline auth keys: api_token, api_base (e.g. https://wiki.example.com/api), optional default_collection_id.
  • Confluence auth keys: api_base, email, api_token, optional default_space_key, default_parent_id. Install with: pip install g-gremlin[docs-confluence]
  • Confluence sugar: blockquotes → panels, [STATUS: ON TRACK] → status lozenge, ::: expand Title blocks.
  • Optional chaining can come later via recipes; today each command stands alone. Deferred: Sheets writeback, Common Room webhook endpoint, richer template gallery.