Telegram
bubbuild/bub
Telegram Bot skill for sending and editing Telegram messages via Bot API.
Resolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results.
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install telegramdesktop/tdesktop perform-task --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/perform-task .claude/skills/perform-task && rm -rf skills-srcUse ~/.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/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .claude/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-taskType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install telegramdesktop/tdesktop perform-task --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/perform-task .agents/skills/perform-task && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .agents/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install telegramdesktop/tdesktop perform-task --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/perform-task .cursor/skills/perform-task && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .cursor/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/telegramdesktop/tdesktop.git --path .agents/skills/perform-task--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install telegramdesktop/tdesktop perform-task --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/perform-task .gemini/skills/perform-task && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .gemini/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install telegramdesktop/tdesktop perform-taskInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/perform-task .github/skills/perform-task && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .github/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add telegramdesktop/tdesktop --skill perform-task -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install telegramdesktop/tdesktop perform-task --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/telegramdesktop/tdesktop.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/perform-task .opencode/skills/perform-task && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "perform-task" agent skill from https://github.com/telegramdesktop/tdesktop/tree/dev/.agents/skills/perform-task into .opencode/skills/perform-task/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "perform-task", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
perform-taskResolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results.
Perform Task is an agent skill from telegramdesktop/tdesktop. Resolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results. Use when the user invokes $perform-task or /perform-task with a known task name, or when the continue scheduler delegates one selected task. Runs standard review lenses with fast applicability bailouts and selects task-specific domain and evidence instruments without selecting additional work.
Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `agents/openai.yaml`, `references/computer-use-testing.md` and `references/phase-prompts.md`).
It sits in Productivity & Automation. It works with Telegram. The repository describes itself as: Telegram Desktop messaging app. The licence is GPL-3.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit d346b42. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Perform Task loads about 3k tokens when it runs, and up to ~35k if it reads all its reference files. Until then it costs about 125 tokens; SKILL.md has 1,571 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
The full file from telegramdesktop/tdesktop at commit d346b42, republished under its GPL-3.0 licence (© telegramdesktop). 1,571 words, ~2,962 tokens.
.claude/skills/perform-task/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.When running in Grok Build, read .grok/ai-workflow-adapter.md completely
before any other host-specific delegation rule and apply its substitutions.
Own exactly one task through its retained change, or a proved
already-satisfied outcome, and a canonical AI Approve or exceptional
Block, or a canonical Split-required result. Do not process the inbox,
create replacement tasks, drain the queue,
select a follow-up, or consolidate pending tasks afterward. The continue
scheduler isolates discovery routing and queue consolidation in fresh workers
after this performer returns.
Read these files completely before phase work:
references/pipeline.md for the authoritative end-to-end runner contract;references/phase-prompts.md for exact leaf prompts and retry rules;.agents/shared/test-loop.md for the implementation/test state machine;.agents/shared/build-lock-recovery.md for bounded exact-checkout Windows
build-lock recovery;references/computer-use-testing.md when UI-driver selection or operation is
relevant.The pipeline reference adapts conflicting generic test-loop mechanics for the external AI worktree and exact-path safety. Its named adapter wins at those points; retain every other test-loop rule.
Run from a Telegram Desktop checkout. Use the host's Python 3 command:
python3 .agents/skills/process-inbox/scripts/workspace.py resolve \
--name <short-slug-or-full-task-id>Use python or py -3 when appropriate. The helper reads the ignored machine
tag, derives the checkout tag, synchronizes clean AI state, and resolves an
exact full id, exact final path slug, or exact normalized friendly title.
Prefer a unique unfinished match over approved history. Never guess among
several unfinished matches; report their full ids.
An interactive invocation requires a nonempty name. If none was supplied, ask
for the friendly short name or full id. A continue delegation always supplies
the full id and explicit workspace values; still resolve and verify them.
If commits.slot_only is nonzero and the slot is clean, run the helper's
publish command and resolve again. A dirty slot is valid only when every
change belongs to this checkout's one in-progress task. Those files are local
resumable phase state; never discard them. Any unrelated dirty or divergent
state is a hard stop.
Inspect the resolved task, readiness, other_active_task, status, and owner.
If another task is already in-progress for this checkout, stop.
If this task is approved, report its completed result and stop.
If it is split-required, report its published split proposal and stop. A
direct invocation leaves routing to the human; a scheduler invocation returns
control so continue can launch the dedicated split worker.
If it is owned by another checkout, stop. Cross-checkout restart is a rare explicit human reassignment, never an implicit steal.
If its dependencies are unfinished, report them and stop without starting.
Inspect task.md for approved source-task prerequisites in addition to
depends_on, then run workspace.py source-lineage --task <full-task-id>
with one --require <source-task-id> for each explicit prerequisite. Require
current_satisfies: true before Phase 1. For start or retry, pass the same
--require arguments so claiming is machine-gated too.
If it is todo and either unclaimed or owned by this checkout, atomically
assign and activate it:
python3 .agents/skills/process-inbox/scripts/workspace.py start \
--task <full-task-id>If it is blocked and owned by this checkout, reopen it locally:
python3 .agents/skills/process-inbox/scripts/workspace.py retry \
--task <full-task-id>Preserve all source recovery, plans, reviews, tests, result, and evidence.
Continue from the first incomplete validated boundary. This creates no
Resume commit.
If it is already in-progress and owned by this checkout, resume it without
another state commit.
Refresh with resolve after each mutation. The source pipeline begins only
after the slot state shows this task in-progress for this checkout. For a new
task, canonical master must already contain its Start commit.
A source-lineage mismatch found before Phase 1 is a pre-phase routing stop, not
a task Block: create no phase artifacts, source edits, retained commit, or
integration task. Return the lineage report to the continue scheduler, which
may safely switch an existing local branch and resume. In a direct interactive
invocation, report it and ask the human. If the mismatch is first discovered
only after Phase 1 has completed, restore every owned/disposable source change
to a clean boundary and publish a genuine blocked result naming the exact
missing source task and appropriate branch evidence. Do not cherry-pick,
rebase, merge, or manufacture the prerequisite. This blocker is task-local;
the scheduler may continue work that does not depend on it.
Execute references/pipeline.md exactly. A task that changes the repository
and is approved produces:
[ai] prefix,
blank line, and Task: <full-task-id>;Approve <full-task-id> commit containing all final AI
artifacts and state.New and unfinished tasks use the single adaptive implement path. Assessment
must first confirm that the request is one cohesive implementation/review/test
unit. If it contains independently useful and independently testable product
boundaries, record Scope: split-required and a concrete split proposal before
source edits. The same result may arise later from the bounded convergence
assessment when the retained implementation proves that one review/evidence
campaign is not coherent. Do not force the broad request through smaller
implementation phases and call it one task. The independent assessment has
veto authority over further implementation, not authority to create, retire,
or rewrite tasks. The performer writes the split result, preserves any owned
implementation and source refs, and publishes it with
finish --status split-required. The checkout scheduler owns the later queue
mutation and implementation transfer. A direct invocation returns the
published proposal to the human.
For a cohesive task, use one mandatory general review, all five standard review
lenses, and a falsifiable evidence plan. On the initial implementation the
general reviewer and all lenses inspect the task and complete diff without
seeing one another's findings. A lens may return a compact
NOT_APPLICABLE immediately after that scan when it proves the diff affects no
mechanism it owns; otherwise it reads the relevant changed files and adjacent
code and returns CLEAN or FINDINGS. The evidence loop
may use static readings, commands and artifacts, unit tests, a standalone probe
or component binary, a Telegram Debug build with logged assertions, an in-app
overlay, Computer Use, screenshots, or any necessary combination. Do not
require a portable account, Telegram executable, or desktop unless a selected
check uses it. Do not weaken a runtime or visual check merely because another
instrument is cheaper.
The general reviewer examines every changed file in full and the evidence plan,
may reject an unsupported NOT_APPLICABLE, require a named domain specialist
or stronger instrument, and cannot defer its own concern. Its approval and
every clean or proved-not-applicable lens result carry forward. A fix
invalidates only the findings, changed invariants, specialists, validations,
and evidence checks it actually affects. Review fixes receive a focused general
delta review plus only those invalidated specialists; they do not restart the
full review or evidence design.
Automatic replay is bounded. If two review verdicts need changes, findings are
not converging, or a fix expands the architecture or owned paths, run the
pipeline's independent convergence assessment instead of another broad round.
It chooses a bounded focused repair, a coherent replan, or RESCOPE_REQUIRED;
unresolved findings are never approved merely to meet the bound. A task whose
desired outcome was already present may finish without a source commit only
after the same general review and evidence loop prove
Outcome: already-satisfied.
Only a genuine exhausted task blocker produces a
canonical Block <full-task-id> commit. Agent interruption, tool loss, and
global environment stops leave the task in-progress with its task-scoped
local state intact for the next invocation.
A repeated evidence setup failure is not exhausted recovery by itself. Follow
the shared directness ladder: forbid the failed command, fixture, probe, or
capture technique and make the next run closer to the changed surface. The configured
test-run cap closes one campaign: preserve prior passes, isolate the unmet
checks, and start at most one focused recovery campaign unless a fresh
assessment proves every direct strategy exhausted. A second campaign cap or a
repeated non-converging focused signature stops automatic work for an explicit
human/convergence decision; it does not start another campaign. A cap and a
TEST_FLAW can never by themselves publish BLOCKED or approval.
A pre-Runner crash or DeadlockDetector event is not an evidence setup failure merely because the scenario did not start. Apply the shared crash diagnostics and debugger fallback before changing an account fixture. An empty or unusable dump requires live debugging after at most one confirmation run; it never supports a fixture verdict.
A locked macOS session is not an environment stop or evidence blocker for a selected Telegram runtime check. Skip interactive Computer Use and complete the same coverage through the in-binary overlay: drive the flow, log/assert, capture widgets or windows, quit, and assess the saved artifacts. Non-app instruments are unaffected.
A Windows build-output lock is not an immediate environment stop. Follow the
shared bounded recovery contract, including exact-path cleanup before builds.
Only its exhausted or unsafe outcome is a global hard stop; it never becomes a
task Block.
Do not report success from a source commit alone. The final AI commit must be canonical. Retry ordinary concurrent-master publication races until success. On a semantic conflict, unsafe checkout, or unreachable remote, preserve resumable state and report a hard stop.
Return a compact result with the full task id, status or hard stop, attempts, touched files, canonical final-publication confirmation, and exact evidence or unverified behavior. Never persist or report commit hashes; the full task id is the only cross-repository link.
© telegramdesktop, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files (references) in .agents/skills/perform-task of telegramdesktop/tdesktop.
Open the folder on GitHubat commit d346b42
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in telegramdesktop/tdesktop, which our catalogue first saw on October 7, 2026.
Perform Task 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Perform Task this skilltelegramdesktop/tdesktop | 33k | 2 repos | ~3k | Automated safety check: Pass | GPL-3.0 | |
| Telegrambubbuild/bub | 1.7k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Send User MessageTinyAGI/tinyagi | 3.6k | — | ~829 | Automated safety check: Pass | MIT | |
| Tlivey49/tlive | 214 | 1 repos | ~1.7k | Automated safety check: Notes | MIT | |
| Tg CLIjackwener/tg-cli | 293 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Pytdbotpytdbot/client | 137 | — | ~4.3k | Automated safety check: Pass | MIT |
bubbuild/bub
Telegram Bot skill for sending and editing Telegram messages via Bot API.
TinyAGI/tinyagi
Send a proactive message to a paired user via their channel (Discord, Telegram, or WhatsApp).
y49/tlive
tlive — remote approvals (Telegram/Feishu/web), live web terminal, and session monitoring for Claude Code / Codex.
jackwener/tg-cli
CLI skill for Telegram to sync chats, search messages, filter keywords, and monitor groups from the terminal
pytdbot/client
Write Telegram bots and userbots with Pytdbot (async TDLib wrapper with high-level helpers; not the Telegram Bot API).
terranc/claude-telegram-bot-bridge
Install and configure the Telegram Skill Bot. An agent skill from terranc/claude-telegram-bot-bridge.
telegramdesktop/tdesktop
Process the local ignored ai-tdesktop inbox into durable, independently testable Telegram Desktop task records while task execution worktrees remain active.
telegramdesktop/tdesktop
Continue autonomous Telegram Desktop development from the shared ai-tdesktop repository.
telegramdesktop/tdesktop
Drive an intent-aware rebase of the current checkout, resolving every conflict by reading the history behind both sides instead of by making the markers disappear.
Works with
Categories
Resolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results. Perform Task is an agent skill from telegramdesktop/tdesktop. Resolve, start or resume, implement, review, test, and publish exactly one existing ai-tdesktop task by short slug or full dated id, including rare blocked retries and split-required results.
Perform Task fits situations like: the user invokes $perform-task; /perform-task with a known task name; the continue scheduler delegates one selected task.
Run `npx skills add telegramdesktop/tdesktop --skill perform-task -a claude-code`. Or copy the skill folder (.agents/skills/perform-task in telegramdesktop/tdesktop) into .claude/skills/perform-task in your project. Claude Code loads it when a task matches its description.
Run `npx skills add telegramdesktop/tdesktop --skill perform-task -a codex`. Or copy the skill folder (.agents/skills/perform-task in telegramdesktop/tdesktop) into .agents/skills/perform-task in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add telegramdesktop/tdesktop --skill perform-task -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/perform-task, .gemini/skills/perform-task, .github/skills/perform-task and .opencode/skills/perform-task in your project.
Going by SKILL.md and its folder, Perform Task needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
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.
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. Review the folder before installing.
Perform Task is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3k tokens (SKILL.md is roughly 12k 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 32k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Perform Task: Telegram (bubbuild/bub, 1.7k stars), Send User Message (TinyAGI/tinyagi, 3.6k stars), Tlive (y49/tlive, 214 stars) and Tg CLI (jackwener/tg-cli, 293 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
telegramdesktop (a GitHub organization) maintains it in telegramdesktop/tdesktop, which has 33,131 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 7, 2026.
Source: telegramdesktop/tdesktop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.