Agent skill

Outcome Completion Agent

by CALLE-AI in CALLE-AI/awesome-phone-call-agents

Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated…

MITAuto-check passed

Install Outcome Completion Agent

skills CLI
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill outcome-completion-agent -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install CALLE-AI/awesome-phone-call-agents outcome-completion-agent --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/outcome-completion-agent .claude/skills/outcome-completion-agent && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
outcome-completion-agent
GitHub stars
107
Token cost
~2.3k tokens
SKILL.md length
1,396 words
Files
8 (incl. scripts, references)
Skills in repo
101
Repo updated
First seen
Licence
MIT

At a glance

Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated…

  • Works in 7 steps: Confirm the user wants this pursued by… → Collect the outcome fields (see Required… → Show a masked preview: the goal, the… → …
  • SKILL.md covers When To Use, When Not To Use, Core Workflow and Required Fields, plus 6 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Outcome Completion Agent is an agent skill from CALLE-AI/awesome-phone-call-agents. Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated limits, follow referrals to parties the user never supplied, and gate the single call that commits the user.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/approval-gate.md`, `references/constraint-evaluation.md` and `references/evidence-schema.md`).

The repository describes itself as: Portable phone-call Agent Skills, apps, examples, adapters, and scheduler recipes for AI agents. The licence is MIT.

Example prompts

  • “/outcome-completion-agent”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Confirm the user wants this pursued by phone, now, and that they accept calls may go to
  2. Collect the outcome fields (see Required Fields). Ask for anything missing. Never infer
  3. Show a masked preview: the goal, the constraints as the agent understood them, the
  4. Loop, one call at a time
  5. Stop conditions, checked before every dial
  6. Exactly one call in the run may commit the user, and only after they approve it. Read
  7. Report using the Output Format below, whether or not the goal was reached.

What it can do on your machine

Read from SKILL.md and the folder at commit 38d4118. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Outcome Completion Agent loads about 2.3k tokens when it runs, and up to ~8.6k if it reads all its reference files. Until then it costs about 82 tokens; SKILL.md has 1,396 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from CALLE-AI/awesome-phone-call-agents at commit 38d4118, republished under its MIT licence (© CALLE-AI). 1,396 words, ~2,309 tokens.

Download SKILL.mdSave it as .claude/skills/outcome-completion-agent/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
outcome-completion-agent
description
Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated limits, follow referrals to parties the user never supplied, and gate the single call that commits the user.
license
MIT

Outcome Completion Agent

Use this skill when the user states an outcome rather than a call, the route to that outcome runs through more than one organisation, and the next organisation is usually named on a call rather than known in advance.

"Get a replacement pallet for the crushed delivery on order BK-7741, before Friday, under $500."

The user has one phone number: the supplier who sent the broken pallet. The supplier is out of stock and names a distributor. The distributor quotes over the limit and names its own depot. The depot can do it. Three organisations, two of which did not exist as far as the agent was concerned when the run began.

outcome-completion-agent is a calling-pattern skill. It adds no backend, no queue and no daemon. It turns one authorized "make this happen" request into a bounded loop of one-off CALL-E calls whose order is decided by what earlier calls established.

When To Use

  • a problem whose owner is unknown: "find out who can actually fix this and get it fixed"
  • a chain of custody: supplier to distributor to depot, carrier to facility to counter, insurer to provider to adjuster
  • a goal with a hard limit attached — a price ceiling, a date, a required reference — where a cheerful "yes" that breaks the limit is a failed outcome
  • any request where the honest answer to "who should we call?" is "ask the first person"

When Not To Use

  • one call, one structured answer. Use a single-call skill; this loop is overhead.
  • a known, priority-ordered candidate list for one opening. Read skills/priority-call-waterfall/SKILL.md instead — one opening, call in order, stop at the first yes.
  • comparison shopping over an enumerable set of same-service vendors (every barber within 4km). If the candidate list is a database or map query, the frontier does not need to grow and this skill's machinery buys nothing.
  • anything email, a web form, or an API can do. A phone call is a real-world side effect and the most expensive way to ask a question.
  • goals with no completion test. If nobody can say what "done" looks like, the loop cannot stop, and a loop that cannot stop must not be given a phone.

Core Workflow

  1. Confirm the user wants this pursued by phone, now, and that they accept calls may go to organisations they did not name.

  2. Collect the outcome fields (see Required Fields). Ask for anything missing. Never infer a phone number, a price ceiling, or a deadline.

  3. Show a masked preview: the goal, the constraints as the agent understood them, the starting phone book, and the call budget. Get explicit confirmation before call one. Always show the parsed constraints back. A price ceiling that failed to parse is a ceiling that will never block anything, and the user is the only one who can catch it.

  4. Loop, one call at a time:

    text
    plan -> (approval, if it commits) -> one call -> evidence -> constraints -> plan
    • plan — pick the next party from the frontier: a party never called, else a party that did not answer and is under its retry cap. Prefer a party named by the call that just happened over one the user listed but nobody has reached.
    • call — exactly one CALL-E call, with a structured result schema. Wait for a terminal status. Read references/evidence-schema.md for the schema every call fills.
    • evidence — record what was established: verdict, facts, blockers, referrals, and any concrete offer. Add referrals with a valid E.164 number to the frontier. Drop referrals without one.
    • constraints — evaluate any offer against the user's limits. Read references/constraint-evaluation.md. A call that completed happily and breaks a hard limit is a failed outcome: keep working.
  5. Stop conditions, checked before every dial:

    • an acceptable offer has been confirmed by the other party → resolved
    • the call budget or the per-party cap is reached → stop and report
    • every lead is exhausted with nothing acceptable → stop and report
  6. Exactly one call in the run may commit the user, and only after they approve it. Read references/approval-gate.md.

  7. Report using the Output Format below, whether or not the goal was reached.

Required Fields

  • goal — one sentence, imperative, with the constraints taken out of it
  • constraints[] — each with kind, description, value, and hard (budget · deadline · required_fact · preference · forbidden). hard: true disqualifies an offer. hard: false only ranks it.
  • organizations[] — the starting phone book: name, phone (E.164), role. One entry is enough; that is the point of the skill.
  • budget — max_calls for the whole outcome and max_calls_per_org. Both are required. A goal-seeking agent with an unbounded phone budget is not a product, and CALL-E accounts are metered.

Phone numbers must be E.164, and must be masked in every summary, preview and report.

Show full SKILL.md (623 more words)Show less

Following A Referral

This is the part that distinguishes this pattern, so it has its own rules.

  • A referral counts only when the person on the call named a number. "Try their head office" without a number is a fact, not a lead.
  • Validate it as E.164 before adding it. A number that cannot be dialled is not a lead, and keeping it puts an entry in front of the planner that can never be actioned.
  • De-duplicate on the number. Two calls naming the same depot must not produce two entries, or the depot gets called twice.
  • Carry the provenance: which call produced this lead, and the reason given. The report has to be able to say "the agent found this one", and the next call should be able to open with "Halden Packaging suggested I call you".
  • A referral is a lead, not an instruction. It still costs a call from the budget, it still goes through the same constraint checks, and it never bypasses the approval gate.

Budgets

Check the budget immediately before dialling, never when planning. An approval can sit overnight; the credit it would spend may be gone by the time it comes back.

Sensible defaults for a metered account: 6 calls per outcome, 2 per organisation. The per-organisation cap is what stops a no-answer loop from consuming the whole budget on one unanswered line.

Never widen a budget mid-run to finish a goal. Stop, report, and let the user decide whether it is worth more calls.

Output Format

Report every run, resolved or not:

  • the goal, restated, and the constraints as they were evaluated
  • every organisation touched, in order: masked number, calls used, final verdict, whether the agent found it or the user supplied it
  • every offer received, with a per-constraint verdict and, for the ones turned down, which constraint they broke
  • the outcome: what was secured, from whom, at what price, by when, and any reference number — or why the run stopped
  • calls used against the budget

Never report an outcome as resolved unless the other party confirmed it on a call the user approved. An offer is not a resolution.

Safety Rules

Read references/safety.md for the full contract. Always:

  • Disclose that the caller is an AI assistant, at the start of every call, before asking anything. If the person asks for a human or asks you to stop: apologise, end the call, record it, and do not call that number again in this run.
  • Gathering calls have no authority. Their script must say so explicitly.
  • One call per run may commit the user, only with prior approval, and only to the exact terms approved.
  • Mask every phone number in output. Never read a credential aloud.
  • Medical, legal, financial and emergency matters are logistics only: ask about times, availability and reference numbers, and give no advice.
  • This skill creates no recurring schedule. Every call is one-shot. To stop a run, stop approving; nothing is committed without an approval, and nothing is queued for later.

Worked Examples

Read references/examples.md for a full run, a run that stops on budget, and the two failure modes that most often get this pattern wrong.

Validating A Result

scripts/check_evidence_schema.py checks one structured_result against the schema and reports what a planner would actually be able to use from it — no network, no credentials, no calls:

bash
python3 scripts/check_evidence_schema.py path/to/result.json

It reports errors (the result is malformed) separately from notes (the result parses, but something in it will be discarded). The notes matter more than they look: a referral whose number is unusable is the difference between an agent that finds the depot and one that stops at the supplier, and nothing else in the run will tell you it was dropped.

Check the checker with python3 scripts/test_check_evidence_schema.py.

© CALLE-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in skills/outcome-completion-agent of CALLE-AI/awesome-phone-call-agents.

  • SKILL.md
  • references/approval-gate.md
  • references/constraint-evaluation.md
  • references/evidence-schema.md
  • references/examples.md
  • references/safety.md
  • scripts/check_evidence_schema.py
  • scripts/test_check_evidence_schema.py

Open the folder on GitHubat commit 38d4118

Compare with similar skills

Outcome Completion Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Outcome Completion Agent compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Outcome Completion Agent this skillCALLE-AI/awesome-phone-call-agents107—~2.3kAutomated safety check: PassMIT
Goalscodewhale-hq/Codewhale41k—~273Automated safety check: PassMIT
Goal Objective DrafterQwenLM/qwen-code28k—~3.5kAutomated safety check: PassApache-2.0
Fable Goalalirezarezvani/claude-skills28k—~2.4kAutomated safety check: PassMIT
Agent Goal Plannerruvnet/ruflo74k2 repos~842Automated safety check: PassMIT
Goal Planruvnet/ruflo74k—~807Automated safety check: NotesMIT

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Questions about Outcome Completion Agent

What does Outcome Completion Agent do?

Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated…. Outcome Completion Agent is an agent skill from CALLE-AI/awesome-phone-call-agents. Own one goal across as many CALL-E calls as it takes, when who to call next depends on what the last call said — read every call as structured evidence, reject offers that break the user's stated limits, follow referrals to parties the user never supplied, and gate the single call that commits the user.

How do I install Outcome Completion Agent in Claude Code?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill outcome-completion-agent -a claude-code`. Or copy the skill folder (skills/outcome-completion-agent in CALLE-AI/awesome-phone-call-agents) into .claude/skills/outcome-completion-agent in your project. Claude Code loads it when a task matches its description.

How do I install Outcome Completion Agent in Codex?

Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill outcome-completion-agent -a codex`. Or copy the skill folder (skills/outcome-completion-agent in CALLE-AI/awesome-phone-call-agents) into .agents/skills/outcome-completion-agent in your project. Codex loads it when a task matches its description.

Can I use Outcome Completion Agent in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CALLE-AI/awesome-phone-call-agents --skill outcome-completion-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/outcome-completion-agent, .gemini/skills/outcome-completion-agent, .github/skills/outcome-completion-agent and .opencode/skills/outcome-completion-agent in your project.

What does Outcome Completion Agent need to run?

Going by SKILL.md and its folder, Outcome Completion Agent needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Outcome Completion Agent access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Outcome Completion Agent safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Outcome Completion Agent use?

Outcome Completion Agent is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Outcome Completion Agent use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.3k tokens, read only when the agent opens those files.

What are the alternatives to Outcome Completion Agent?

Skills that share tags, products or a category with Outcome Completion Agent: Goals (codewhale-hq/Codewhale, 41k stars), Goal Objective Drafter (QwenLM/qwen-code, 28k stars), Fable Goal (alirezarezvani/claude-skills, 28k stars) and Agent Goal Planner (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Outcome Completion Agent?

CALLE-AI (a GitHub organization) maintains it in CALLE-AI/awesome-phone-call-agents, which has 107 GitHub stars. The repository holds 101 skills in this directory. The repository was last updated on October 10, 2026.

Source: CALLE-AI/awesome-phone-call-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.