Agent skill

Speculative Pipeline

by hashgraph-online in hashgraph-online/awesome-codex-plugins

A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays.

Apache-2.0Auto-check passed

Install Speculative Pipeline

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill speculative-pipeline -a claude-code

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

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins speculative-pipeline --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/speculative-pipeline .claude/skills/speculative-pipeline && 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
speculative-pipeline
GitHub stars
1.3k
Token cost
~2.9k tokens
SKILL.md length
1,188 words
Files
1
Skills in repo
716
Repo updated
First seen
Licence
Apache-2.0

At a glance

A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays.

  • Works in 5 steps: Stage 2 starts after a 1.5-hour offset.… → Stage 2 generates plans from whatever… → Stage 1 keeps refining specs. When Stage… → …
  • SKILL.md covers Core Principle, The Pattern, Example: 3-Stage Pipeline and Choosing Delay Values, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Speculative Pipeline is an agent skill from hashgraph-online/awesome-codex-plugins. A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays. The leader begins first, and followers start after a delay, building from whatever partial output exists. Combined with convergence loops, early follower output self-corrects as upstream artifacts solidify. Cuts total pipeline time dramatically -- a 3-stage pipeline that takes 12 hours sequentially can finish in roughly 7 hours with speculative-pipeline staggering. Triggers…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.

Example prompts

  • “speculative-pipeline”
  • “staggered pipeline”
  • “parallel prompts with delay”
  • “/speculative-pipeline”

Workflow steps

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

  1. Stage 2 starts after a 1.5-hour offset. By then, Stage 1 has produced a meaningful set of partial specs.
  2. Stage 2 generates plans from whatever specs are available. Some plans will be built on incomplete information.
  3. Stage 1 keeps refining specs. When Stage 2 loops back for its next pass, it picks up
  4. Stage 3 starts after a 3-hour offset. By then, both specs and plans exist in draft form.
  5. All stages self-correct through iteration. Each pass re-reads the latest upstream artifacts. Mistakes caused

What it can do on your machine

Read from SKILL.md and the folder at commit 3e1456a. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    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

Speculative Pipeline loads about 2.9k tokens when it runs. Until then it costs about 165 tokens; SKILL.md has 1,188 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~165
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its Apache-2.0 licence (© hashgraph-online). 1,188 words, ~2,929 tokens.

Download SKILL.mdSave it as .claude/skills/speculative-pipeline/SKILL.md (or your agent's skills folder).
name
speculative-pipeline
description
A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays. The leader begins first, and followers start after a delay, building from whatever partial output exists. Combined with convergence loops, early follower output self-corrects as upstream artifacts solidify. Cuts total pipeline time dramatically -- a 3-stage pipeline that takes 12 hours sequentially can finish in roughly 7 hours with speculative-pipeline staggering. Triggers: "speculative-pipeline", "staggered pipeline", "parallel prompts with delay", "overlap pipeline stages", "faster pipeline".

Speculative-pipeline Strategy

Run pipeline stages with staggered timing instead of sequentially. The leader starts first; followers start after a configurable delay and build from whatever upstream output exists at that point. Combined with convergence loops, followers self-correct as upstream artifacts arrive and stabilize.

Core Principle

Start downstream work early with partial upstream output. Convergence loops correct the errors introduced by working from incomplete input.

The insight is that waiting for perfect upstream output is wasteful. A follower working from 80% of the upstream artifacts will produce output that is ~60-70% correct on the first pass. But with convergence loops running, the follower re-reads the upstream artifacts on each iteration and corrects course. By the time the leader finishes, the follower is already most of the way done.


The Pattern

Sequential (Traditional)
Stage 1: Specs     ████████████████████                          (5 hours)
Stage 2: Plans                         ████████████████          (4 hours)
Stage 3: Implement                                     ████████  (3 hours)
                   ─────────────────────────────────────────────
                   Total: 12 hours
Speculative-pipeline (Staggered)
Stage 1: Specs     ████████████████████                          (5 hours)
Stage 2: Plans            ████████████████                       (4 hours, started 1.5h after Stage 1)
Stage 3: Implement              ████████████                     (3 hours, started 3h after Stage 1)
                   ─────────────────────────────────────────────
                   Total: ~7 hours
Why It Works
  1. Stage 2 starts after a 1.5-hour offset. By then, Stage 1 has produced a meaningful set of partial specs.
  2. Stage 2 generates plans from whatever specs are available. Some plans will be built on incomplete information.
  3. Stage 1 keeps refining specs. When Stage 2 loops back for its next pass, it picks up the newly completed specs and adjusts its plans accordingly.
  4. Stage 3 starts after a 3-hour offset. By then, both specs and plans exist in draft form.
  5. All stages self-correct through iteration. Each pass re-reads the latest upstream artifacts. Mistakes caused by working from partial input are washed out on subsequent passes.

The key mechanism is convergence -- the iterative loop that re-reads inputs each pass. Without convergence loops, speculative-pipeline would produce garbage. With them, early errors wash out over iterations.


Example: 3-Stage Pipeline

Directory Structure
context/
├── specs/              # Stage 1 output: implementation-agnostic specs
├── plans/              # Stage 2 output: framework-specific plans
├── impl/               # Stage 3 output: implementation tracking
└── prompts/
    ├── 001-generate-specs.md       # Stage 1 prompt
    ├── 002-generate-plans.md       # Stage 2 prompt
    └── 003-implement.md            # Stage 3 prompt
Terminal Commands

Open three terminal windows (or use tmux panes):

bash
# Terminal 1: Specs from reference materials (leader -- starts immediately)
{LOOP_TOOL} context/prompts/001-generate-specs.md -n 5 -t 2h

# Terminal 2: Plans from specs (follower -- starts after 1-hour delay)
{LOOP_TOOL} context/prompts/002-generate-plans.md -n 5 -t 2h -d 1h

# Terminal 3: Implementation from plans (follower -- starts after 2-hour delay)
{LOOP_TOOL} context/prompts/003-implement.md -n 10 -t 1h -d 2h

Parameter reference:

  • -n 5 -- Run up to 5 convergence iterations
  • -t 2h -- Time budget per iteration (max total time = iterations x budget)
  • -d 1h -- Delay before starting (speculative-pipeline offset)

Replace {LOOP_TOOL} with your convergence loop runner (any script or tool that repeatedly executes a prompt against the codebase, committing between iterations).

What Happens Chronologically
TimeStage 1 (Specs)Stage 2 (Plans)Stage 3 (Implement)
0:00Starts. Reads refs, begins generating specs.Waiting (1.5h delay).Waiting (3h delay).
1:30Iteration 1 complete. ~50% of specs written. Committed.Starts. Reads partial specs, begins generating plans.Waiting.
3:00Iteration 2. Specs ~80% complete.Iteration 1 complete. Plans based on partial specs. Some plans will need correction.Starts. Reads partial specs + plans, begins implementing.
4:00Iteration 3. Specs ~92% complete, converging.Iteration 2. Re-reads updated specs. Corrects plans. Plans ~65% correct.Iteration 1 complete. Some implementation based on incomplete plans.
5:00Converged. Specs complete. Done.Iteration 3. Re-reads final specs. Plans ~88% correct.Iteration 2. Re-reads corrected plans. Fixes implementation.
5:30--Iteration 4. Plans converged. Done.Iteration 3. Implementation ~75% correct.
7:00----Iteration 4-5. Implementation converges. Done.

Result: ~7 hours total versus ~12 hours sequential.


Choosing Delay Values

The delay determines how much upstream work exists when the follower starts. Too short and the follower wastes iterations on garbage input. Too long and you lose the time savings.

Guidelines
Upstream Stage DurationRecommended DelayRationale
1-2 hours15-30 minutesShort stages produce useful partial output quickly
2-4 hours1 hourEnough time for the first iteration to complete and commit
4+ hours1-2 hoursFirst iteration should have substantial output
Rules of Thumb
  1. Delay >= 1 upstream iteration. The follower should not start until the leader has completed at least one full iteration and committed results.
  2. Delay < 50% of upstream duration. If the delay is longer than half the upstream time, the time savings are marginal.
  3. More follower iterations compensate for shorter delays. If you start the follower early (aggressive delay), give it more iterations to converge.

Multi-Stage Pipelines (4+ Stages)

For pipelines with more than 3 stages, stagger each stage relative to Stage 1:

bash
# 5-stage pipeline example
{LOOP_TOOL} {PROMPT_001} -n 5 -t 2h           # Stage 1: starts immediately
{LOOP_TOOL} {PROMPT_002} -n 5 -t 2h -d 1h     # Stage 2: 1h delay
{LOOP_TOOL} {PROMPT_003} -n 8 -t 1h -d 2h     # Stage 3: 2h delay
{LOOP_TOOL} {PROMPT_004} -n 8 -t 1h -d 3h     # Stage 4: 3h delay
{LOOP_TOOL} {PROMPT_005} -n 10 -t 45m -d 4h   # Stage 5: 4h delay

Notice the pattern:

  • Later stages get more iterations (they need more correction cycles)
  • Later stages get shorter time budgets per iteration (less work per stage)
  • Delays increase linearly (each stage offset by roughly 1 hour)

When Speculative-pipeline Works Best

Good Fit
  • Long pipelines (3+ stages): The time savings scale with pipeline depth
  • Stages that share a git repo: Followers read upstream commits automatically
  • Stages with convergence loops: The self-correction mechanism is essential
  • Specs that are mostly stable after 1-2 iterations: Partial specs are useful early
Show full SKILL.md (462 more words)Show less
Poor Fit
  • Stages with hard dependencies: If Stage 2 literally cannot start without Stage 1's complete output (e.g., code generation that requires a fully resolved type system), the follower will produce only errors
  • Single-iteration stages: Without convergence loops, there is no self-correction
  • Very short pipelines (2 stages, <1 hour each): The overhead of staggering is not worth the small time savings

Monitoring Speculative-pipeline Execution

What to Watch
  1. Follower diff sizes per iteration. If the follower's diffs are large on every iteration (not decreasing), it is thrashing -- the delay was too short or the upstream output is too unstable.
  2. Follower convergence rate. The follower should converge within 1-2 iterations of the leader finishing. If it takes many more, the stages may have a hard dependency.
  3. Git commit frequency. Both leader and follower should be committing regularly. If commits stall, the agent may be stuck.
Convergence Signals

A speculative-pipeline pipeline has converged when:

  • All stages have completed their iteration loops
  • The final iteration of each stage produces minimal diffs
  • Build and test gates pass on the merged output
Thrashing Detection

Thrashing = the follower keeps making large changes because upstream output keeps changing.

Signs of thrashing:

  • Follower diff sizes do not decrease across iterations
  • Follower reverts changes it made in previous iterations
  • Build failures increase instead of decreasing

Fix thrashing by:

  1. Increasing the delay (give the leader more time to stabilize)
  2. Reducing follower iterations (let upstream settle first)
  3. Adding a "wait for upstream convergence" gate between stages

Combining with Agent Teams

In multi-agent setups, speculative-pipeline applies at the pipeline level, not the agent team level:

Pipeline Level (speculative-pipeline timing):
  Stage 1 (Specs)     → Single agent or agent team
  Stage 2 (Plans)     → Single agent or agent team (starts after delay)
  Stage 3 (Implement) → Agent team dispatched via Agent tool (starts after delay)

Each stage can internally use agent teams (multiple teammates working in parallel on different domains), but the stages themselves are staggered using speculative-pipeline timing.

Do not confuse:

  • Leader-follower: Pipeline stages overlapping in time
  • Agent teams: Multiple agents working in parallel within a single stage

They are orthogonal and composable.


Implementation Checklist

When setting up a speculative-pipeline pipeline:

  • Define the pipeline stages (typically: specs, plans, implement)
  • Create a prompt file for each stage with explicit input/output directories
  • Ensure each stage reads from upstream directories and writes to its own directory
  • Configure convergence loop for each stage with appropriate iteration counts
  • Choose delays: first follower at ~1 upstream iteration, subsequent at ~1h increments
  • Set up terminal sessions (one per stage) or use tmux
  • Monitor: watch for convergence (decreasing diffs) vs thrashing (constant large diffs)
  • After all stages complete, run full build + test validation on the merged output

Cross-References

  • prompt-pipeline -- How to design the prompt files that each stage executes
  • convergence-monitoring -- How to detect convergence vs ceiling in each stage
  • methodology -- Where speculative-pipeline fits in the Hunt lifecycle
  • validation-first -- Validation gates that run after each stage completes
  • context-architecture -- Directory structure that stages read from and write to

© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/JuliusBrussee/blueprint/skills/speculative-pipeline of hashgraph-online/awesome-codex-plugins.

Open the folder on GitHubat commit 3e1456a

Compare with similar skills

Speculative Pipeline 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.

Speculative Pipeline compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Speculative Pipeline this skillhashgraph-online/awesome-codex-plugins1.3k—~2.9kAutomated safety check: PassApache-2.0
Speculative Namingsgl-project/sglang37k2 repos~1.6kAutomated safety check: PassApache-2.0
Classroom Stage Design MethodTHU-MAIC/OpenMAIC40k—~1.4kAutomated safety check: PassMIT
Stage Tamagotchi Godot Csharpmoeru-ai/airi50k—~677Automated safety check: PassMIT
OpenMAIC Stage Document MapTHU-MAIC/OpenMAIC40k—~2.4kAutomated safety check: PassMIT
Speculation Rulesthedaviddias/Front-End-Checklist74k—~509Automated safety check: PassMIT

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Questions about Speculative Pipeline

What does Speculative Pipeline do?

A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays. Speculative Pipeline is an agent skill from hashgraph-online/awesome-codex-plugins. A pipeline execution strategy where downstream stages start before upstream stages finish, using staggered timing with configurable delays.

How do I install Speculative Pipeline in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill speculative-pipeline -a claude-code`. Or copy the skill folder (plugins/JuliusBrussee/blueprint/skills/speculative-pipeline in hashgraph-online/awesome-codex-plugins) into .claude/skills/speculative-pipeline in your project. Claude Code loads it when a task matches its description.

How do I install Speculative Pipeline in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill speculative-pipeline -a codex`. Or copy the skill folder (plugins/JuliusBrussee/blueprint/skills/speculative-pipeline in hashgraph-online/awesome-codex-plugins) into .agents/skills/speculative-pipeline in your project. Codex loads it when a task matches its description.

Can I use Speculative Pipeline 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 hashgraph-online/awesome-codex-plugins --skill speculative-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/speculative-pipeline, .gemini/skills/speculative-pipeline, .github/skills/speculative-pipeline and .opencode/skills/speculative-pipeline in your project.

What does Speculative Pipeline need to run?

SKILL.md names no scripts, command-line tools or credentials: Speculative Pipeline is instructions for the agent only.

Does Speculative Pipeline 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 Speculative Pipeline 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. Review the folder before installing.

What licence does Speculative Pipeline use?

Speculative Pipeline is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Speculative Pipeline use?

About 2.9k 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.

What are the alternatives to Speculative Pipeline?

Skills that share tags, products or a category with Speculative Pipeline: Speculative Naming (sgl-project/sglang, 37k stars), Classroom Stage Design Method (THU-MAIC/OpenMAIC, 40k stars), Stage Tamagotchi Godot Csharp (moeru-ai/airi, 50k stars) and OpenMAIC Stage Document Map (THU-MAIC/OpenMAIC, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Speculative Pipeline?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.