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Get Started Free →Use DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a benchmark, inspect DeepChat runtime state, or manage DeepChat through the CLI.
.claude/skills/thinkinaixyz-deepchat-cli/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-19 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -16% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 152% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 98% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 144% | 0% |
Use the bundled deepchat command to ask the running DeepChat main process to perform supported operations. The main process remains the sole owner of providers, credentials, Skills, MCP servers, artifacts, Agent runs, and approvals.
deepchat <domain> <verb>. Put --json, --jsonl,--timeout, and all domain options after the domain and verb.
exec call. Do not use pipes, redirection, command separators,command substitution, environment assignments, or shell wrappers around deepchat.
an unquoted command.
--json for one result and --jsonl for streaming or benchmark collection. Use text modeonly when its output will be returned directly to the user.
is injected only after the command has passed the normal shell permission check.
renderer approval; wait for that decision and never attempt to manufacture confirmation data.
deepchat help or deepchat <domain> <verb> --help only when the options below areinsufficient. Do not probe undocumented routes.
--artifact <id> and inspect metadatawith artifact describe.
--file, --out, --overwrite, artifact get, or artifact delete. Agent callerscannot upload arbitrary local bytes, download artifact bytes, or choose output paths.
agent run or run watch. An Agent cannot recursively create a detached Agent run,and waiting on its own currently executing run would deadlock it. Use run get for a nonblocking snapshot or run cancel to request cancellation.
application can render or reuse it.
textdeepchat system status --json deepchat system capabilities --json deepchat system doctor --json deepchat provider list --enabled-only --json deepchat model list --provider <provider-id> --json deepchat model config-get --provider <provider-id> --model <model-id> --json deepchat model invoke --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl
Always discover provider and model IDs rather than guessing them. model invoke is a raw provider call: it does not create a chat session, run tools, or start an Agent loop.
textdeepchat image generate --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl deepchat video generate --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl deepchat audio speak --provider <provider-id> --model <model-id> --text <quoted-text> --jsonl deepchat audio transcribe --provider <provider-id> --model <model-id> --artifact <artifact-id> --json deepchat ocr status --json deepchat ocr extract --artifact <artifact-id> --json deepchat artifact describe --id <artifact-id> --json
Use the provider/model lists to choose a compatible runtime. OCR is local and does not require a provider. OCR text is returned inline and is not written to the artifact spool.
Read-only operations:
textdeepchat settings get --json deepchat skill list --json deepchat mcp list --json
Agent callers may request renderer approval for preference-only settings, query-free HTTPS Skill installation, and adding a new disabled HTTPS remote MCP configuration. Only perform one when it directly satisfies the user's request:
textdeepchat settings set --key <public-key> --value <json-scalar> --json deepchat skill install --url <https-url> --json deepchat mcp add --name <server-name> --stdin --json
The Agent setting allowlist is limited to presentation preferences such as font size/family, artifact effects, auto-scroll, notifications, and copy-with-reasoning. Agent Skill URLs cannot carry credentials, query parameters, or fragments. The main process classifies MCP input before approval and rejects stdio commands, non-HTTPS endpoints, headers, authorization bindings, or configurations too large to review safely. Provider/model configuration, credential writes, local Skill archives, Skill enable/disable/removal, MCP update/runtime control/removal, and every destructive operation require the DeepChat UI or a human terminal.
benchmark.
offline availability. ocr clear-cache initializes the resource graph but does not start the OCR helper, so classify the next extraction from its reported pre-extraction runtime state.
rate-limited and bounded by the main process.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-19 | fail→pass | 5,904 | 1,621 | -73% | 1 | 1 | 0% | 944 | 1,390 | +47% | 0 | 0 | — |
case-01 | fail→fail | 12,416 | 16,643 | +34% | 1 | 1 | 0% | 2,064 | 1,485 | -28% | 0 | 0 | — |
case-02 | fail→fail | 4,955 | 5,412 | +9% | 1 | 1 | 0% | 51 | 1,502 | +2845% | 0 | 0 | — |
case-03 | fail→fail | 5,901 | 6,081 | +3% | 1 | 1 | 0% | 818 | 1,611 | +97% | 0 | 0 | — |
case-04 | fail→pass | 14,140 | 4,558 | -68% | 1 | 1 | 0% | 2,498 | 2,090 | -16% | 0 | 0 | — |
case-05 | fail→fail | 24,800 | 13,614 | -45% | 1 | 1 | 0% | 1,839 | 2,419 | +32% | 0 | 0 | — |
case-06 | fail→fail | 8,878 | 5,395 | -39% | 1 | 1 | 0% | 1,522 | 1,550 | +2% | 0 | 0 | — |
case-07 | fail→pass | 5,257 | 9,881 | +88% | 1 | 1 | 0% | 846 | 2,132 | +152% | 0 | 0 | — |
case-08 | fail→fail | 6,388 | 9,469 | +48% | 1 | 1 | 0% | 400 | 1,940 | +385% | 0 | 0 | — |
case-09 | pass→pass | 5,246 | 2,425 | -54% | 1 | 1 | 0% | 702 | 1,593 | +127% | 0 | 0 | — |
case-10 | fail→pass | 7,434 | 5,016 | -33% | 1 | 1 | 0% | 1,014 | 2,009 | +98% | 0 | 0 | — |
case-11 | fail→fail | 4,725 | 5,767 | +22% | 1 | 1 | 0% | 852 | 1,530 | +80% | 0 | 0 | — |
case-12 | pass→pass | 13,904 | 3,282 | -76% | 1 | 1 | 0% | 2,053 | 1,825 | -11% | 0 | 0 | — |
case-13 | fail→fail | 9,984 | 9,059 | -9% | 1 | 1 | 0% | 379 | 1,860 | +391% | 0 | 0 | — |
case-14 | fail→pass | 5,992 | 6,319 | +5% | 1 | 1 | 0% | 913 | 2,226 | +144% | 0 | 0 | — |
case-15 | fail→pass | 5,489 | 3,461 | -37% | 1 | 1 | 0% | 888 | 1,772 | +100% | 0 | 0 | — |
case-16 | fail→pass | 6,326 | 6,364 | +1% | 1 | 1 | 0% | 910 | 2,379 | +161% | 0 | 0 | — |
case-17 | fail→pass | 7,341 | 3,745 | -49% | 1 | 1 | 0% | 1,137 | 1,427 | +26% | 0 | 0 | — |
case-18 | pass→fail | 8,485 | 4,815 | -43% | 1 | 1 | 0% | 1,478 | 1,415 | -4% | 0 | 0 | — |
case-20 | pass→pass | 14,933 | 2,826 | -81% | 1 | 1 | 0% | 2,334 | 1,639 | -30% | 0 | 0 | — |
case-21 | pass→pass | 8,602 | 6,206 | -28% | 1 | 1 | 0% | 1,573 | 2,328 | +48% | 0 | 0 | — |
case-22 | pass→pass | 6,815 | 4,393 | -36% | 1 | 1 | 0% | 1,280 | 2,077 | +62% | 0 | 0 | — |
case-23 | pass→pass | 5,379 | 4,085 | -24% | 1 | 1 | 0% | 989 | 1,959 | +98% | 0 | 0 | — |
case-24 | pass→pass | 5,364 | 4,195 | -22% | 1 | 1 | 0% | 794 | 1,920 | +142% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 24 cases were attempted, and 15 counted toward the lift figure. The other 9 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +29 percentage points is the difference between those two pass rates over the 15 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.