Add draft_dismiss_recommendations

.claude/rules/adloop.md

@@ -79,7 +79,7 @@ You have access to AdLoop MCP tools that connect Google Ads, Reddit Ads and Goog
 - `get_ad_performance` returns full `headlines` and `descriptions` lists for RSAs, plus `ad_group_ad.policy_summary.approval_status`, `review_status` and `policy_topics` (topic names only) per ad. Ads that are `DISAPPROVED` (cannot serve) or `APPROVED_LIMITED` (serving restricted) are listed in `policy_issues` with their spend and flagged in `insights[]`; compact mode adds `by_approval_status` counts.
 - `get_campaign_performance` returns `metrics.search_impression_share`, `metrics.search_budget_lost_impression_share` and `metrics.search_rank_lost_impression_share` as fractions (0.25 = 25%) with matching `*_pct` percentages. Google caps the reported values: 0.0999 means below 10% share, 0.9001 means above 90% lost. They are `null` for campaigns that do not serve on Search (Display, Video, PMax, ...) or had no impressions, which means "does not apply", not zero. `budget_limited_converters` and `insights[]` flag converting campaigns losing 20% or more of impressions to budget: those can absorb more budget, rank-lost share instead points at bids, ad relevance and quality.
 - `get_change_history` returns changes newest first with counts `by_resource_type`, `by_client`, `by_user` and `by_day`. Google Ads keeps 30 days of change history, so an older start date is moved forward (see `notes`). `insights[]` flag auto-applied recommendations and budget or bidding changes. `truncated: true` means the limit was hit; narrow the range or filters to see older changes.
-- `get_recommendations` returns `estimated_improvement` per recommendation (potential minus base metrics) and `insights[]` that flag budget-increase recommendations, whose projected gain comes from spending more.
+- `get_recommendations` returns each recommendation's `recommendation.id` (what `draft_dismiss_recommendations` takes) and `estimated_improvement` per recommendation (potential minus base metrics) and `insights[]` that flag budget-increase recommendations, whose projected gain comes from spending more.
 - PMax tools: `get_pmax_performance` returns `insights[]` flagging weak ad strength and zero-conversion asset groups. `segments.ad_network_type` includes MIXED — a Google catch-all for most PMax traffic. Full channel splits (Search vs YouTube vs Display vs Discover) are not available via the API.
 - `get_pmax_assets` returns `by_status` and `by_field_type` summaries. Note: per-asset performance labels (BEST/GOOD/LOW) are not available for PMax assets in the Google Ads API. Use `get_detailed_asset_performance` for quality signals via top combinations.
 - `get_audience_performance` works for campaigns with explicit audience targeting. PMax audience targeting is automatic and may not appear in this report. When the results include SEARCH campaigns, `insights[]` reminds you that custom segments cannot be attached to them (see the compatibility matrix below) — relay that constraint instead of proposing impossible pairings.
@@ -317,6 +317,7 @@ Conversions that happen offline (a sales call, a lead that turned into a deal) g
 | `add_to_negative_keyword_list` | Append keywords to an EXISTING shared negative keyword list (does NOT add) | `shared_set_id` (from `get_negative_keyword_lists`), keyword list, `match_type` |
 | `attach_shared_set_to_campaigns` | Attach an EXISTING shared set (e.g. shared negative keyword list) to one or more campaigns. Use after creating a campaign to inherit pre-built negatives. | `shared_set_id` (from `get_negative_keyword_lists`), `campaign_ids` list |
 | `detach_shared_set_from_campaigns` | Detach a shared set from one or more campaigns. Removes only the linkage; the shared set and its keywords stay intact. | `shared_set_id`, `campaign_ids` list |
+| `draft_dismiss_recommendations` | Dismiss Google recommendations the user has decided not to take. Nothing in the account changes and Google can show them again later; unknown or already dismissed IDs are refused. No validate-only mode: the dry run re-reads the account and checks each one is still active | `recommendation_ids` (`recommendation.id` from `get_recommendations`) |
 | `draft_demographic_targeting` | Propose demographic criteria (age, gender, parental status, income range) at ad group or campaign level. Defaults to EXCLUSION (`negative=True`). | exactly one of `ad_group_id` or `campaign_id`, at least one of `age_ranges`/`genders`/`parental_statuses`/`income_ranges`, optional `negative` (default True) |
 | `draft_audience_attachment` | Attach audiences to a campaign or ad group as OBSERVATION (default: bids and reporting, reach unchanged), TARGETING (ads only reach the audiences; double confirmation) or exclusion. Refuses incompatible pairings, Search lists too small to target, audiences at both campaign and ad group level, and Performance Max | exactly one of `campaign_id` or `ad_group_id`; any of `user_list_ids`, `segment_ids`, `custom_audience_ids`, `combined_audience_ids`; `mode` observation/targeting; `exclude` |
 | `draft_ai_max_settings` | Draft AI Max controls for one Search campaign: `enable_ai_max`, per-ad-group `disable_search_term_matching`, text and final-URL asset automation. Refuses a plan that would switch AI Max on while an automation it was never told about keeps running; an explicitly requested automation asks for a double confirmation. | `campaign_id`, optional `enable_ai_max`, optional `disable_search_term_matching`, optional `ad_group_ids`, optional `include_paused_ad_groups`, optional `text_asset_automation`, optional `final_url_expansion` |
@@ -657,6 +658,7 @@ Reddit's structure is campaign → ad group (budget, bid, pixel, targeting) →
 4. Use `estimated_improvement` to prioritize: recommendations with >1 estimated additional conversion are worth investigating
 5. For keyword recommendations, call `get_keyword_performance` to check existing keyword overlap before acting
 6. Present recommendations grouped by type with your assessment of each — the user should understand which ones are genuinely helpful vs which ones just increase Google's revenue
+7. For the ones the user decides not to take, offer `draft_dismiss_recommendations` with their IDs, so they stop reappearing. Dismiss only what the user turned down: a dismissal is not a verdict you make on their behalf
 
 ### When user asks about audience performance or targeting
 

.cursor/rules/adloop.mdc

@@ -81,7 +81,7 @@ You have access to AdLoop MCP tools that connect Google Ads, Reddit Ads and Goog
 - `get_ad_performance` returns full `headlines` and `descriptions` lists for RSAs, plus `ad_group_ad.policy_summary.approval_status`, `review_status` and `policy_topics` (topic names only) per ad. Ads that are `DISAPPROVED` (cannot serve) or `APPROVED_LIMITED` (serving restricted) are listed in `policy_issues` with their spend and flagged in `insights[]`; compact mode adds `by_approval_status` counts.
 - `get_campaign_performance` returns `metrics.search_impression_share`, `metrics.search_budget_lost_impression_share` and `metrics.search_rank_lost_impression_share` as fractions (0.25 = 25%) with matching `*_pct` percentages. Google caps the reported values: 0.0999 means below 10% share, 0.9001 means above 90% lost. They are `null` for campaigns that do not serve on Search (Display, Video, PMax, ...) or had no impressions, which means "does not apply", not zero. `budget_limited_converters` and `insights[]` flag converting campaigns losing 20% or more of impressions to budget: those can absorb more budget, rank-lost share instead points at bids, ad relevance and quality.
 - `get_change_history` returns changes newest first with counts `by_resource_type`, `by_client`, `by_user` and `by_day`. Google Ads keeps 30 days of change history, so an older start date is moved forward (see `notes`). `insights[]` flag auto-applied recommendations and budget or bidding changes. `truncated: true` means the limit was hit; narrow the range or filters to see older changes.
-- `get_recommendations` returns `estimated_improvement` per recommendation (potential minus base metrics) and `insights[]` that flag budget-increase recommendations, whose projected gain comes from spending more.
+- `get_recommendations` returns each recommendation's `recommendation.id` (what `draft_dismiss_recommendations` takes) and `estimated_improvement` per recommendation (potential minus base metrics) and `insights[]` that flag budget-increase recommendations, whose projected gain comes from spending more.
 - PMax tools: `get_pmax_performance` returns `insights[]` flagging weak ad strength and zero-conversion asset groups. `segments.ad_network_type` includes MIXED — a Google catch-all for most PMax traffic. Full channel splits (Search vs YouTube vs Display vs Discover) are not available via the API.
 - `get_pmax_assets` returns `by_status` and `by_field_type` summaries. Note: per-asset performance labels (BEST/GOOD/LOW) are not available for PMax assets in the Google Ads API. Use `get_detailed_asset_performance` for quality signals via top combinations.
 - `get_audience_performance` works for campaigns with explicit audience targeting. PMax audience targeting is automatic and may not appear in this report. When the results include SEARCH campaigns, `insights[]` reminds you that custom segments cannot be attached to them (see the compatibility matrix below) — relay that constraint instead of proposing impossible pairings.
@@ -319,6 +319,7 @@ Conversions that happen offline (a sales call, a lead that turned into a deal) g
 | `add_to_negative_keyword_list` | Append keywords to an EXISTING shared negative keyword list (does NOT add) | `shared_set_id` (from `get_negative_keyword_lists`), keyword list, `match_type` |
 | `attach_shared_set_to_campaigns` | Attach an EXISTING shared set (e.g. shared negative keyword list) to one or more campaigns. Use after creating a campaign to inherit pre-built negatives. | `shared_set_id` (from `get_negative_keyword_lists`), `campaign_ids` list |
 | `detach_shared_set_from_campaigns` | Detach a shared set from one or more campaigns. Removes only the linkage; the shared set and its keywords stay intact. | `shared_set_id`, `campaign_ids` list |
+| `draft_dismiss_recommendations` | Dismiss Google recommendations the user has decided not to take. Nothing in the account changes and Google can show them again later; unknown or already dismissed IDs are refused. No validate-only mode: the dry run re-reads the account and checks each one is still active | `recommendation_ids` (`recommendation.id` from `get_recommendations`) |
 | `draft_demographic_targeting` | Propose demographic criteria (age, gender, parental status, income range) at ad group or campaign level. Defaults to EXCLUSION (`negative=True`). | exactly one of `ad_group_id` or `campaign_id`, at least one of `age_ranges`/`genders`/`parental_statuses`/`income_ranges`, optional `negative` (default True) |
 | `draft_audience_attachment` | Attach audiences to a campaign or ad group as OBSERVATION (default: bids and reporting, reach unchanged), TARGETING (ads only reach the audiences; double confirmation) or exclusion. Refuses incompatible pairings, Search lists too small to target, audiences at both campaign and ad group level, and Performance Max | exactly one of `campaign_id` or `ad_group_id`; any of `user_list_ids`, `segment_ids`, `custom_audience_ids`, `combined_audience_ids`; `mode` observation/targeting; `exclude` |
 | `draft_ai_max_settings` | Draft AI Max controls for one Search campaign: `enable_ai_max`, per-ad-group `disable_search_term_matching`, text and final-URL asset automation. Refuses a plan that would switch AI Max on while an automation it was never told about keeps running; an explicitly requested automation asks for a double confirmation. | `campaign_id`, optional `enable_ai_max`, optional `disable_search_term_matching`, optional `ad_group_ids`, optional `include_paused_ad_groups`, optional `text_asset_automation`, optional `final_url_expansion` |
@@ -659,6 +660,7 @@ Reddit's structure is campaign → ad group (budget, bid, pixel, targeting) →
 4. Use `estimated_improvement` to prioritize: recommendations with >1 estimated additional conversion are worth investigating
 5. For keyword recommendations, call `get_keyword_performance` to check existing keyword overlap before acting
 6. Present recommendations grouped by type with your assessment of each — the user should understand which ones are genuinely helpful vs which ones just increase Google's revenue
+7. For the ones the user decides not to take, offer `draft_dismiss_recommendations` with their IDs, so they stop reappearing. Dismiss only what the user turned down: a dismissal is not a verdict you make on their behalf
 
 ### When user asks about audience performance or targeting
 

README.md

@@ -306,6 +306,7 @@ All write operations follow a **draft → preview → confirm** workflow. Nothin
 | `draft_update_custom_conversion_goal` | Rename a custom conversion goal and/or replace its action list (list replace, not append) |
 | `draft_assign_custom_conversion_goal` | Point a campaign at a custom conversion goal (`goal_config_level = CAMPAIGN`) |
 | `draft_clear_custom_conversion_goal` | Put a campaign back on the account-level goals (rollback) |
+| `draft_dismiss_recommendations` | Dismiss Google recommendations you won't take, so they stop reappearing (Google can show them again later) |
 | `pause_entity` | Pause a campaign, ad group, ad, keyword or PMax asset group |
 | `enable_entity` | Re-enable a paused entity |
 | `remove_entity` | Permanently remove an entity (irreversible — prefers pause). Supports keywords, negative keywords, ads, ad groups, campaigns. |

src/adloop/ads/read.py

@@ -843,6 +843,10 @@ def get_recommendations(
         pot_conversions = _round_metric(getattr(pot, "conversions", 0))
 
         entry = {
+            # The ID (last segment of the resource name) is what
+            # draft_dismiss_recommendations takes.
+            "recommendation.id": rec.resource_name.rsplit("/", 1)[-1],
+            "recommendation.resource_name": rec.resource_name,
             "recommendation.type": rec_type,
             "recommendation.campaign": rec.campaign,
             "recommendation.ad_group": rec.ad_group or "",