AI-Engineering-Coach's full system prompt: 2 versions, 2,723 characters. Audited against AISPA.
The full text of 2
prompts is reproduced below,
2,723 characters in all, each read
instruction by instruction against the eight
AISPA dimensions.
Nothing was flagged as working against the person on
the other end.
---
id: instruction-bloat
name: Instruction Bloat
group: prompt-quality
severity: medium
scope: sessions
requiresIdeContext: true
version: 1
tags: [tokens, instructions, context, cost]
thresholds:
maxBytes: 4000
minBloated: 1
---
# Description
Detects oversized `.github/copilot-instructions.md` (or equivalent) files. Custom instructions are prepended to **every** request's system prompt — large files inflate input tokens on every turn, often by thousands of tokens that are never relevant to the current task.
# When Triggered
{{extra.bloatedSessions}} workspace(s) have custom-instruction files larger than {{thresholds.maxBytes}} bytes (largest: {{extra.maxBytes}} bytes). Every request in those workspaces pays the bloat cost on input tokens.
# How to Improve
Trim `.github/copilot-instructions.md` to the essentials: language/framework conventions, code style, "do not" rules, and pointers to longer docs. Move long examples and rationale into separate files referenced via `#file:`. Keep the always-on payload under ~4 KB.
# Examples
{{extra.maxBytes}} bytes — largest custom-instructions file across {{extra.totalSessions}} workspace(s)
# Detection Logic
```detect
scan: sessions
match: true
aggregate: count
stats: instructionBloatStats(allSessions, thresholds.maxBytes)
bloatedSessions: stats.bloatedSessions
maxBytes: stats.maxBytes
totalSessions: stats.totalSessions
withInstructionsCount: stats.withInstructionsCount
emitCount: stats.bloatedSessions
emitTotal: stats.totalSessions
check: stats.bloatedSessions >= thresholds.minBloated
examples: {{maxBytes}} bytes (workspace-level)
```
---
id: mcp-tool-bloat
name: Tool / MCP Bloat
group: tool-mastery
severity: medium
scope: sessions
version: 2
tags: [tools, mcp, context-window]
thresholds:
maxToolsPerSession: 40
minSessions: 3
---
# Description
Detects sessions with an unusually large number of distinct tools invoked — a proxy for oversized tool catalogs that inflate every request's system prompt. Each registered tool adds tokens regardless of whether it's used.
# When Triggered
{{count}} session(s) used more than {{thresholds.maxToolsPerSession}} distinct tools. Large tool sets add silent overhead to every prompt.
# How to Improve
Trim the active toolset: disable rarely-used MCP servers, scope tool sets per workspace, and use tool groups so only relevant tools are loaded for the task at hand. Aim for under 40 active tools per session.
# Examples
{{flatUnique(reqs, "toolsUsed")}} tools in one session
# Detection Logic
```detect
scan: sessions
match: flatUnique(reqs, "toolsUsed") > thresholds.maxToolsPerSession
aggregate: count
check: count >= thresholds.minSessions
examples: {{flatUnique(reqs, "toolsUsed")}} tools
```
Questions about AI-Engineering-Coach's system prompt
Does AI-Engineering-Coach's system prompt contain instructions that work against the user?
No. Nothing in AI-Engineering-Coach's system prompt was flagged as working against the person the product is talking to. That is a clean result across all eight AISPA dimensions, not an absence of checking — the full text was read instruction by instruction.
How long is AI-Engineering-Coach's system prompt?
2,723 characters across 2 prompts on this page. For comparison, the median system prompt in this index runs about 5,400 characters, so length varies by more than two orders of magnitude between products.
How many versions of AI-Engineering-Coach's system prompt are on record?
2. Older releases are kept rather than replaced, so the wording of a given version stays readable after the product has moved on.
Where did this AI-Engineering-Coach system prompt come from?
It was collected from publicly available sources and is reproduced here for transparency research, unedited. This site does not extract prompts from products itself.
How was AI-Engineering-Coach's system prompt audited?
Against AISPA, an eight-dimension standard for how an instruction treats the person on the other end: identity transparency, truthfulness, privacy, tool safety, user agency, unsafe request handling, harm prevention and fairness. This audit was ai audit. The method is described in the paper behind the standard.
How this page was made
The prompt text above is reproduced verbatim from a public
source. Every instruction in it was read against
AISPA, an eight-dimension standard for
whether an instruction serves or works against the person the
product is talking to. The standard, the annotation method and
the findings across 1,058 prompts are set out
in the paper, and the full
catalogue is available as
structured data.
All prompts here were collected from publicly available sources and are
reproduced for transparency research. Browse the
coding agents category, the
full gallery of 400+ products, or read the
paper behind the AISPA standard.