What does the Okr AI skill do?

Draft and track a strategic OKR charter — turn a human's plain-language goal into ONE Objective + 2-5 measurable Key Results, link existing tasks, and route the commit to a human sponsor. Use whenever the user wants to set a strategic goal / OKR / objective, "立个 OKR", or "把 X 推到 GA". Executes via the `cloud okr` CLI.

Why use Okr on TypingMind?

Because you install it once and use it with any model. Okr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Okr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/cloud/catalog/skills/okr. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Okr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Okr?

As many as you like. As long as a model supports skills, you can use Okr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Okr AI skill free?

Yes. It is published on GitHub by Prismer-AI under the MIT license. You only pay your own AI provider for the tokens you use.

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Okr by Prismer-AI — AI Skill for Any LLM

OKR

Use this skill to draft an OKR charter from a human's goal: one Objective, 2-5 Key Results, each with a baseline→target and a real evidence source, plus links to the tasks that move them. Every operation goes through the cloud okr CLI — never tell the user an objective was created / committed / scored unless the command actually returned an id and state.

You draft and propose. The human commits. That split is the whole point of this skill (see ⛔ hard rules).

When to use

The user wants to set a strategic goal: "let's set an OKR for Q3", "立个 OKR", "make reliability our objective this cycle", "把搜索推到 GA".
A long-running objective should become a tracked Objective + Key Results, not a loose kind=goal card. (When the user says "make this a goal", draft an objective charter here, not a plain task.)
You need to link existing tactical tasks to the Key Result they serve.
The user wants to see OKR health — the objective tree with KR progress.

If the request is a single tactical deliverable ("review this PR", "write the report"), that's the tasks skill, not this one. Strategic outcome → here; tactical card under an existing objective → tasks with the KR link.

Charter drafting methodology

From a human's plain-language goal, draft ONE Objective + 2-5 Key Results. Before drafting, ask for whatever is missing:

Outcome — what observable end-state defines success? (the Objective title)
Deadline / cycle — which cycle does this belong to? (--cycle 2026-Q3)
Owner — which agent/human drives it? (--owner <imUserId>)
Sponsor — which human/admin stands behind it? (--sponsor <human imUserId>) — required for a committed objective.
Per KR: a baseline → target, and a measurable source. Today's KNOWN sources are ONLY:
- task acceptance — a task/milestone KR whose progress is the count of linked tasks that pass acceptance.
- IMMetricEvent metric binding — a metric KR bound to an existing metric stream (--metric-namespace --metric-name --metric-agg).
- human-confirm — a qualitative KR a human scores explicitly with a value + evidence.

Then:

Draft the objective (agent proposes — it is NOT yet committed):

bash
cloud okr objective create \
  --workspace "$PRISMER_WORKSPACE_ID" \
  --title "Search is GA-ready" \
  --type committed \
  --narrative "Definition of done: search ships to all users with p95 < 300ms and zero P0s." \
  --cycle 2026-Q3 \
  --owner <imUserId> \
  --sponsor <human imUserId>

Propose each KR with baseline/target/unit/direction/weight + an evidence policy:

bash
# metric-backed KR (bound to a real IMMetricEvent stream)
cloud okr kr add <objectiveId> \
  --title "p95 search latency under 300ms" \
  --type metric --baseline 480 --target 300 --unit ms --direction decrease --weight 2 \
  --metric-namespace search.latency --metric-name p95 --metric-agg last \
  --evidence "IMMetricEvent search.latency:p95, last value per cycle"

# task-backed KR (progress = linked tasks that pass acceptance)
cloud okr kr add <objectiveId> \
  --title "Ship 4 launch-blocker fixes" \
  --type task --baseline 0 --target 4 --direction increase \
  --evidence "count of linked tasks with passing acceptance"

Link existing tasks to the KR they serve (don't create unscoped strategic tasks):

bash
cloud okr link <objectiveId> <keyResultId> <taskId>

STOP and hand the commit to the human sponsor. Print the objective id + KR ids and say: "Charter drafted. @ (human) — review and cloud okr objective commit <id> when you approve." Do not commit it yourself.

⛔ Hard rules

These are enforced server-side; violating them returns a 403 you cannot work around.

NEVER commit an objective yourself. cloud okr objective commit requires a human sponsor; an agent caller gets AGENT_CANNOT_COMMIT. Your job ends at draft + propose. Surface the objective and ask the human sponsor to commit.
A committed-type objective REQUIRES a human/admin sponsor (--sponsor <human imUserId>). Without one, commit returns SPONSOR_MUST_BE_HUMAN. An aspirational objective may skip the sponsor.
NEVER score a qualitative KR without an explicit, human-confirmed value + evidence. Use cloud okr kr recompute <krId> --value <n> --evidence <ref> and only with a value the human actually gave you. Metric/task KRs recompute from their real source automatically — don't hand-feed numbers there.
Bind KRs ONLY to today's sources — task acceptance, IMMetricEvent metric binding, or human-confirm. Do NOT invent token/spend/credit targets, CRM pipelines, or analytics metrics — those data sources do not exist (FROZEN). A KR whose evidence you can't name is not a KR; ask the human how it will be measured.
Do NOT create unscoped strategic tasks. Tactical work for an objective is an existing task linked to a KR via cloud okr link. If strategic work has no task yet, draft the objective/KR first, then create the task (via the tasks skill) and link it.

Lifecycle back-half

After an objective is committed it runs through committed → graded → archived:

Check-ins — you (an agent) MAY draft a check-in. It snapshots the score + each KR's current/status. cloud okr objective checkin <objectiveId> [--note "<t>"] [--confidence 0.6] [--decision continue|rescope|add-resource|pause|cancel].
Grade and archive are HUMAN decisions. cloud okr objective grade <id> and cloud okr objective archive <id> return AGENT_CANNOT_GRADE (403) for an agent caller — surface the objective and ask the human to grade. Grade freezes the score (it stops moving even if a KR's evidence changes). An archived objective is read-only.

Check-in --decision, --confidence, and the reward/resource shapes carry no token/credit meaning — there is no compensation here.

FROZEN / out of scope

This skill draws ONE Objective + its KRs and links tasks. It does NOT propose, create, or mutate any of the following — they are explicitly out of scope for release203 and have no endpoints here:

Guardrails — no guardrail proposals or activations.
Resource / budget allocation — no credit/budget/resource grants.
Scenario packs — none.
Proactive / recurring check-ins — you record a check-in only when asked; there is no auto-scheduler.
Compensation — no reward/bonus economics (the grade carries no payout).

If the user asks for any of these, say it's not part of the OKR charter flow yet rather than improvising one.

CLI Reference

Objectives

bash
# Draft (agent proposes — NOT committed)
cloud okr objective create --workspace <id> --title "<outcome>" \
  [--type committed|aspirational] [--narrative "<DoD>"] [--cycle 2026-Q3] \
  [--owner <imUserId>] [--sponsor <human imUserId>] [--parent <objectiveId>] [--confidence 0.7]

cloud okr objective list --workspace <id> [--state <state>]
cloud okr objective get <objectiveId>

# HUMAN/SPONSOR ONLY — an agent caller gets AGENT_CANNOT_COMMIT
cloud okr objective commit <objectiveId>
cloud okr objective close <objectiveId> [--score 0.8]

Key Results

bash
cloud okr kr add <objectiveId> --title "<measurable result>" \
  [--type metric|task|milestone|qualitative] \
  [--baseline <n>] [--target <n>] [--unit <u>] \
  [--direction increase|decrease|maintain|binary] [--weight <n>] \
  [--metric-namespace <ns> --metric-name <name> --metric-agg avg|sum|last|count] \
  [--evidence "<policy>"] [--source assigned|agent-proposed]

# Qualitative KR scoring — human-confirmed value + evidence ONLY
cloud okr kr recompute <keyResultId> [--value <n>] [--evidence <ref>]

--source defaults to agent-proposed (you, the agent, are drafting). Pass --source assigned only when the human explicitly assigned the KR. --metric-namespace and --metric-name must be given together to bind a metric source.

Linking + reading

bash
cloud okr link <objectiveId> <keyResultId> <taskId>   # scope a task to a KR
cloud okr insights --workspace <id>                    # the OKR tree + KR progress (never fabricated)

Output reporting

After any state-changing command, echo back the id and the state the service returned (not the state you expected). Example:

Drafted objective cmobj... (state draft) with 3 KRs. @ — cloud okr objective commit cmobj... to commit.

If a command exits non-zero, surface the error code verbatim — especially AGENT_CANNOT_COMMIT / SPONSOR_MUST_BE_HUMAN, which mean a human must act. Never fabricate an objective/KR id or a KR value — if you didn't run the command or it failed, say so.

Publisher	Prismer-AI
Repository	`PrismerCloud`
Skill name	`okr`
Stars	1.6K
Forks	17
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Okr

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

OKR

When to use

Charter drafting methodology

⛔ Hard rules

Lifecycle back-half

FROZEN / out of scope

CLI Reference

Objectives

Key Results

Linking + reading

Output reporting

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

OKR

When to use

Charter drafting methodology

⛔ Hard rules

Lifecycle back-half

FROZEN / out of scope

CLI Reference

Objectives

Key Results

Linking + reading

Output reporting

Frequently asked questions

Related AI Skills

Set up your own AI workspace now