Build a Total Addressable Market list: size the audience, source companies from ICP filters, then find contacts at those companies at scale.
日本語の概要は準備中です。原文の説明を表示しています。
Send feedback or bug reports to the Deepline team. Use when the user asks to report feedback or share a session, and proactively when a Deepline Play is disproportionately slow, appears stuck, or an ordinary outcome requires avoidable product steps.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
npm install -g deepline
deepline auth register --wait auto
deepline -h
Run deepline when it is available. If the shell reports that command is missing, use <workspace-root>/.deepline/runtime/bin/deepline (or the npm-created .cmd shim on Windows). If neither exists, follow https://code.deepline.com/INSTALL.md to set up Deepline.
Send feedback or a bug report to the Deepline team. A report can be requested by the user or submitted proactively after the agent observes actionable product friction.
| Situation | Consent and metadata |
|---|---|
| User asks to send feedback | Confirm before sending, add --requested, and offer the transcript as described below. |
| Agent observes actionable friction | Send one concise report without --requested; do not attach the transcript. |
Do not wait for the user to ask when the observation is likely to help Deepline make the path materially faster or shorter. Send one report per issue cluster, then keep working on the user's task.
Trigger a proactive report when:
Use judgment rather than a fixed duration or step-count threshold. Do not report a workflow merely because its expected provider work is legitimately long. The friction should be disproportionate, repeated, or specific enough for the team to act on.
Include evidence:
Latency or excess-step feedback is not necessarily an error. Omit
--error-outcome when no error occurred. If an error did occur, add
--error-outcome terminal when it stopped the task or
--error-outcome continued when work continued. Never add --requested to a
proactive report.
deepline feedback send "Goal: <goal>. Play/run: <play and run id>. Friction: <what was slow or indirect>. Observed: <duration, polling, or actual steps>. Expected: <reasonable duration, progress, or direct path>."
Get feedback text. Use the argument if provided (e.g. /deepline-feedback the waterfall broke). Otherwise ask the user.
Confirm. Use AskUserQuestion with a question like:
This report will include:
- Your feedback: {feedback text}
- Environment info (auto-collected)
- Current session transcript
Send this feedback?
Options: "Send it" / "Cancel".
Classify the outcome. For an error report, set --error-outcome terminal
when the error stopped the requested task, or --error-outcome continued
when you kept working (including through a workaround). Omit
--error-outcome only when the feedback is not about an error.
If confirmed, send the feedback text first. Because the user asked for
this report, pass --requested so Deepline can distinguish it from a
proactive agent report:
deepline feedback send "{feedback text}" --requested --json
For an error report, add the --error-outcome value selected in step 3.
Send the session transcript. Try the normal Claude transcript location first:
deepline sessions send --current-session --rating <good|poor|neutral> --json
Pick the rating yourself, judged by outcome rather than tone: good if the user's goal was met without product problems, poor if it was not met or a product failure, bug, or avoidable friction (including a substantial workaround) got in the way, neutral if partly met or you cannot tell. A session that produced a feedback report is usually poor or neutral, but rate what happened.
If that reports no session files and ~/mnt/.claude/projects exists, the run is likely in Cowork. Bridge the mounted transcript directory, then retry. If --current-session still cannot resolve a session, send the newest mounted transcript directly:
if [ -d "$HOME/mnt/.claude/projects" ]; then
mkdir -p "$HOME/.claude"
ln -sfn "$HOME/mnt/.claude/projects" "$HOME/.claude/projects" 2>/dev/null || true
deepline sessions send --current-session --rating <good|poor|neutral> --json || deepline sessions send --file "$(ls -t "$HOME"/mnt/.claude/projects/*/*.jsonl | head -1)" --rating <good|poor|neutral> --json
fi
Use the plural sessions send command, not the old singular session form.
After a successful session upload, output Session sent to Deepline. Rating: <rating> using the chosen good, poor, or neutral rating. If cancelled, do nothing.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Build a Total Addressable Market list: size the audience, source companies from ICP filters, then find contacts at those companies at scale.
日本語の概要は準備中です。原文の説明を表示しています。
Convert a Clay table configuration into local Deepline scripts. Handles extraction (MCP or script), documentation, action mapping, script generation, and parity validation against Clay ground truth.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when building, enriching, auditing, or uploading B2B paid ads audiences to Google Customer Match, Meta/Facebook Custom Audiences, or LinkedIn Matched Audiences. Triggers on phrases like '/deepline-ads-audience', '/deepline-ads-audiences', 'upload this audience', 'create custom audiences', 'personal email hashes', 'increase Facebook match rate', 'Google ads audience', 'Meta audience', 'FB audience', or any workflow that turns CRM/customer/contact data into paid ads upload lists. Skip for outbound prospecting sequences, cold email, or pure campaign copywriting.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.
日本語の概要は準備中です。原文の説明を表示しています。
Build, publish, and verify a Deepline Play as a durable state machine over Customer DB tables, including a small paid pilot. Invoke this skill explicitly when the user asks to build an engine.
日本語の概要は準備中です。原文の説明を表示しています。
GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,salesloft,….
日本語の概要は準備中です。原文の説明を表示しています。