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configure-channel

Configure and prove a chat channel with non-interactive one-liners; secrets only as SecretRefs.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name configure-channel description Configure and prove a chat channel with non-interactive one-liners; secrets only as SecretRefs. Configure a channel Never print or persist secret values; channel tokens enter config only as SecretRefs, or through the in-session connect_channel flow where the operator types the secret into a masked prompt. Never hand-edit config files on disk. Every run ends with the observable Prove result or an exact explanation of why it could not be proven. Gather openclaw channels list --all openclaw channels status openclaw config get channels --json # "Config path not found" is normal before first setup Confirm the exact config path before writing — key names differ per channel ( channels.telegram.botToken , channels.discord.token , ...): openclaw config schema --json | jq '.properties.channels.properties.telegram' Mutate Preferred shell path — token staged as an env var on the gateway process or in a 0600 file, wired as a SecretRef (Telegram example): openclaw config set channels.telegram.botToken --ref-provider default --ref-source env --ref-id TELEGRAM_BOT_TOKEN openclaw config set channels.telegram.allowFrom '["+15555550123"]' --strict-json Multi-field changes in one validated write: openclaw config patch --stdin <<'JSON' { channels: { telegram: { enabled: true, groupPolicy: "allowlist" } } } JSON In-session alternative: call the connect_channel tool action with the channel id — the operator enters the token in a masked prompt, never in chat. Avoid openclaw channels add --token <value> : it puts the secret in argv and process listings. Repair openclaw doctor --non-interactive openclaw channels status --deep Apply openclaw doctor --fix --non-interactive only after approval, then re-check status. Prove Send one real, clearly labeled test message and confirm delivery from the command result (use --dry-run first to inspect the payload): openclaw message send --channel telegram --target <chatId> --message "OpenClaw channel test — please ignore" --dry-run openclaw message send --channel telegram --target <chatId> --message "OpenClaw channel test — please ignore" If sending fails, report the exact account, permission, destination, or network blocker without exposing credentials. Report State the channel and account changed, the exact config paths written (never values), the test destination, and the observed delivery result. List any remaining operator action. Further reference: https://docs.openclaw.ai/channels/telegram (and the matching page for other channels)
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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